| Entries |
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| 20080199072 | IMAGE PROCESSING DEVICE AND METHOD, LEARNING DEVICE AND METHOD, RECORDING MEDIUM, AND PROGRAM - With the present invention, data continuity is used at the time of converting an input image into high-quality image data with higher quality than the input image data, to obtain processing results which are more accurate and have higher precision. A class tap extracting unit ( | 08-21-2008 |
| 20090154795 | INTERACTIVE CONCEPT LEARNING IN IMAGE SEARCH - An interactive concept learning image search technique that allows end-users to quickly create their own rules for re-ranking images based on the image characteristics of the images. The image characteristics can include visual characteristics as well as semantic features or characteristics, or may include a combination of both. End-users can then rank or re-rank any current or future image search results according to their rule or rules. End-users provide examples of images each rule should match and examples of images the rule should reject. The technique learns the common image characteristics of the examples, and any current or future image search results can then be ranked or re-ranked according to the learned rules. | 06-18-2009 |
| 20090161947 | IMAGE PROCESSING DEVICE AND METHOD, LEARNING DEVICE AND METHOD, PROGRAM, AND RECORDING MEDIUM - An image processing device includes: a smoothing section configured to extract a smoothing tap and smooth a target image on the basis of pixel values within the tap, the smoothing tap being of variable size and including plural pixels centered on each target pixel of the image; a class tap extracting section configured to extract a class tap including plural pixels centered on each target pixel in the smoothed image; a class code determining section configured to generate a code corresponding to a characteristic of variation of pixel values within the class tap, and determine a class code including a size of the smoothing tap and the code; and a pixel value computing section configured to read tap coefficients corresponding to the determined class code, and multiply pixel values forming a prediction tap extracted from the smoothed image, by the tap coefficients to calculate pixel values of a processed image. | 06-25-2009 |
| 20090285472 | DATA PROCESSING APPARATUS AND DATA PROCESSING METHOD - A data processing apparatus processes input data and outputs the processed data. The data processing apparatus includes a data processing section and a real-time learning section. The data processing section processes the input data by a predetermined processing method and outputs the processed data. The real-time learning section controls such that the processing method is learned in real time and the data processing section processes the input data by the learned processing method, so that the output data is improved as time elapses. | 11-19-2009 |
| 20100080449 | Learning Method for Article Storage Facility - A learning method is disclosed for an article storage facility having an article storage rack including article storage units arranged in a rack lateral width direction and a vertical direction, a vertically movable lift, and a horizontal travel carriage associated with the vertically movable lift. A frontal view camera is positioned with respect to the article transfer device such as to capture an image of a detected member provided for each of the storage units from a rack fore-and-aft direction. An angular view camera is positioned with respect to the article transfer device such as to be displaced relative to the frontal view camera in the rack lateral width direction or the vertical direction and such as to capture an image of a detected member from a direction at an angle relative to the rack fore-and-aft direction. And vertical direction correction information, rack lateral width correction information and extending and retracting distance correction information are derived based from image information. | 04-01-2010 |
| 20100254594 | SKETCH GENERATING SYSTEM AND METHOD FOR GENERATING SKETCH BASED ON IMAGE - A sketch generating system and a method for generating a sketch based on an image are provided. The system includes: a sketch database and a generating subsystem. The sketch database stores local image samples and corresponding local sketch units in different categories. The generating subsystem extracts geometrical features from an input image, retrieves local image units from the input image according to the geometrical features; as to each local image unit retrieved, searches the sketch database for a local sketch unit corresponding to a local image sample having a largest similarity value with the local image unit, and combines all local sketch units found to form one sketch. | 10-07-2010 |
| 20100278419 | INFORMATION PROCESSING APPARATUS AND METHOD, AND PROGRAM - An information processing apparatus includes a feature amount extraction unit extracting a feature amount of each frame of an image, a maximum likelihood state series estimation unit estimating maximum likelihood state series using the feature amount, a highlight label generation unit generating highlight label series with respect to the attention detector learning content, and a learning unit learning the highlight detector that is the state transition probability model using learning label series that is a pair of the maximum likelihood state series obtained from the attention detector learning content and the highlight label series. | 11-04-2010 |
| 20100290699 | Landmarks from Digital Photo Collections - Methods and systems for automatic detection of landmarks in digital images and annotation of those images are disclosed. A method for detecting and annotating landmarks in digital images includes the steps of automatically assigning a tag descriptive of a landmark to one or more images in a plurality of text-associated digital images to generate a set of landmark-tagged images,learning an appearance model for the landmark from the set of landmark-tagged images, and detecting the landmark in a new digital image using the appearance model. The method can also include a step of annotating the new image with the tag descriptive of the landmark. | 11-18-2010 |
| 20100303342 | FINDING ICONIC IMAGES - Iconic images for a given object or object category may be identified in a set of candidate images by using a learned probabilistic composition model to divide each candidate image into a most probable rectangular object region and a background region, ranking the candidate images according to the maximal composition score of each image, removing non-discriminative images from the candidate images, clustering highest-ranked candidate images to form clusters, wherein each cluster includes images having similar object regions according to a feature match score, selecting a representative image from each cluster as an iconic image of the object category, and causing display of the iconic image. The composition model may be a Naïve Bayes model that computes composition scores based on appearance cues such as hue, saturation, focus, and texture. Iconic images depict an object or category as a relatively large object centered on a clean or uncluttered contrasting background. | 12-02-2010 |
| 20100316283 | METHOD FOR EXTRACTING SPATIAL KNOWLEDGE FROM AN INPUT SIGNAL USING COMPUTATIONAL MANIFOLDS - A processor architecture for a learning machine is presented which uses a massive array of processing elements having local, recurrent connections to form global associations between functions defined on manifolds. Associations between these functions provide the basis for learning cause-and-effect relationships involving vision, audition, tactile sensation and kinetic motion. Two arbitrary input signals hold each other in place in a manifold association processor and form the basis of short-term memory. | 12-16-2010 |
| 20110026810 | IMAGE ANALYZING APPARATUS, IMAGE ANALYZING METHOD, AND COMPUTER READABLE MEDIUM - Provided is an image analyzing apparatus for efficiently performing detection of an object and tracking of a specified object, including a feature value recording section that records a plurality of reference feature values different in type from each other; a feature value extracting section that extracts a plurality of feature values different in type from each other, from each of a plurality of moving image constituent images included in a moving image; an object extracting section that extracts an object from the moving image constituent images, based on a degree of matching of the plurality of extracted feature values with respect to the plurality of reference feature values recorded in the feature value recording section; a reference feature value calculating section that calculates, from the plurality of reference feature values recorded in the feature value recording section, a plurality of reference feature values adjusted to the feature values of the extracted object, to a predetermined degree corresponding to the type; and a feature value updating section that updates the plurality of reference feature values recorded in the feature value recording section, with the plurality of reference feature values calculated by the reference feature value calculating section. | 02-03-2011 |
| 20110038531 | LEARNING STRING TRANSFORMATIONS FROM EXAMPLES - Techniques are described to leverage a set of sample or example matched pairs of strings to learn string transformation rules, which may be used to match data records that are semantically equivalent. In one embodiment, matched pairs of input strings are accessed. For a set of matched pairs, a set of one or more string transformation rules are learned. A transformation rule may include two strings determined to be semantically equivalent. The transformation rules are used to determine whether a first and second string match each other. | 02-17-2011 |
| 20110044533 | VISUALIZING AND UPDATING LEARNED EVENT MAPS IN SURVEILLANCE SYSTEMS - Techniques are disclosed for visually conveying an event map. The event map may represent information learned by a surveillance system. A request may be received to view the event map for a specified scene. The event map may be generated, including a background model of the specified scene and at least one cluster providing a statistical distribution of an event in the specified scene. Each statistical distribution may be derived from data streams generated from a sequence of video frames depicting the specified scene captured by a video camera. Each event may be observed to occur at a location in the specified scene corresponding to a location of the respective cluster in the event map. The event map may be configured to allow a user to view and/or modify properties associated with each cluster. For example, the user may label a cluster and set events matching the cluster to always (or never) generate an alert. | 02-24-2011 |
| 20110123100 | Predicting States of Subjects - Methods for predicting states of a subject are presented. For example, a method for predicting states of a subject includes obtaining training data comprising a plurality of variables, obtaining training states associated with the training data, and forming a predictive model according to the training data and the training states, the predictive model predictive of the training states. The forming of the predictive model includes extracting one or more hidden components from the training data. The extracting of the one or more hidden components includes regression analysis including determining one or more relationships between the one or more hidden components and the plurality of variables, and determining one or more relationships between the one or more hidden components and the training states. A number of the one or more hidden components is less than a number of the plurality of variables and greater than a number of the training states. | 05-26-2011 |
| 20110229016 | INTRODUCTION SYSTEM, METHOD OF INTRODUCTION, AND INTRODUCTION PROGRAM - An introduction system is capable of identifying, with a high degree of precision, applicants who fulfill recruiter's requirements. An applicant identification unit | 09-22-2011 |
| 20110274344 | Systems and methods for manifold learning for matting - Systems for manifold learning for matting are disclosed, with methods and processes for making and using the same. The embodiments disclosed herein provide a closed form solution for solving the matting problem by a manifold learning technique, Local Linear Embedding. The transition from foreground to background is characterized by color and texture variations, which should be captured in the alpha map. This intuition implies that neighborhood relationship in the feature space should be preserved in the alpha map. By applying Local Linear Embedding using the disclosed embodiments, the local image variations can be preserved in the embedded manifold, which is the resulting alpha map. Without any strong assumption, such as color line model, the disclosed embodiments can be easily extended to incorporate other features beyond RGB color features, such as gradient and texture information. | 11-10-2011 |
| 20120008858 | IMAGE PROCESSING - An image segmentation method has a training phase and a segmentation phase. In the training phase, a frame of pixellated data from a camera is processed using information on camera characteristics to render it camera independent. The camera independent data are processed using a chosen value of illuminant spectral characteristics to derive reflectivity data of the items in the image. Pixels of high reflectivity are established. Then, using data from the high reflectivity pixels, the actual illuminant spectral characteristics are established. The illuminant data are then processed to determine information on the illumination of the scene represented by the frame of pixellated data to derive reflectivity data of the scene. The segmentation phase comprises operating on a subsequent frame of pixellated data to render it camera independent and using the determined illumination information to process the camera independent data to determine reflectivity data of the scene to derive a foreground mask. | 01-12-2012 |
| 20120020550 | IMAGE PROCESSING APPARATUS AND METHOD, AND PROGRAM - The present disclosure provides an image processing apparatus, including: a recognition section adapted to recognize, based on a learning result obtained by learning of a learning image regarding a predetermined object, the object in a predetermined frame of an input image formed from a plurality of frames which are continuous in time; and a setting section adapted to set a parameter to be used for a process to be carried out for a later frame which is later in time than the predetermined frame of the input image in response to a difference in image information between an object image, which is an image in a region of the object recognized in the predetermined frame, and the learning image; the recognition section recognizing the object in the later frame for which the process is carried out based on the parameter set by the setting section. | 01-26-2012 |
| 20120106834 | BACKGROUND MODEL LEARNING SYSTEM FOR LIGHTING CHANGE ADAPTATION UTILIZED FOR VIDEO SURVEILLANCE - Surveillance systems often encounter great challenges from lighting variations, especially for those inspecting outdoor environments. To construct a surveillance system robust to various background scene changes, including lighting variations, a strategy of background model learning is widely adopted. Based on this strategy, many approaches have been proposed in decades to represent background scenes by statistical models and to adapt background changes over time into the models. However, the focus of most background model learning research is put on adaptation of scene vibrations in to background, as well as of gradual lighting variations. For the background model adaptation to drastic lighting changes, many background model learning approaches are often inefficient. As a result, false alarms in foreground detection are issued under such quick lighting changes. To suppress this kind of false alarms, a new system design of background model learning is proposed. | 05-03-2012 |
| 20120114226 | IMAGE PROCESSING DEVICE AND METHOD, DATA PROCESSING DEVICE AND METHOD, PROGRAM, AND RECORDING MEDIUM - A tentative eigenprojection matrix (# | 05-10-2012 |
| 20120134576 | AUTOMATIC RECOGNITION OF IMAGES - Presented is a method of automatically performing an action, based on graphical input. The method comprises: receiving, for a user, an input image; comparing the input image with the contents of a user-customized database comprising a plurality of records, each record representing a predefined class of image, wherein the user has previously associated records in the database with respective specified actions; attempting to recognize the image, based on the similarity of the input image to one of the predefined classes of image represented in the user-customised database; and if the image is recognized, performing the action previously associated by the user with the class. Also presented is apparatus for recognizing an image and a method of constructing a user-customized database. | 05-31-2012 |
| 20120250981 | INFORMATION PROCESSING DEVICE, INFORMATION PROCESSING METHOD, AND PROGRAM - An information processing device includes a learning unit that performs, using an action performed by an object and an observation value of an image as learning data, learning of a separation learning model that includes a background model that is a model of the background of the image and one or more foreground model(s) that is a model of a foreground of the image, which can move on the background, in which the background model includes a background appearance model indicating the appearance of the background, and at least one among the one or more foreground model(s) includes a transition probability, with which a state corresponding to the position of the foreground on the background is transitioned by an action performed by the object corresponding to the foreground, for each action, and a foreground appearance model indicating the appearance of the foreground. | 10-04-2012 |
| 20120257818 | SYSTEMS AND METHODS FOR DATA FUSION MAPPING ESTIMATION - Systems and methods are disclosed for generating a probability density to estimate the probability that an event will occur in a region of interest. The methods input spatial event data comprising one or more events occurring in the region of interest along with auxiliary data related to the region of interest. The auxiliary data comprises non-event data having spatial resolution such that the probability density estimate for the region of interest is calculated based on a function of the auxiliary data and the event data. In particular, the auxiliary data is used to generate a penalty functional used in the calculation of the probability density estimate. | 10-11-2012 |
| 20120263375 | METHOD AND DEVICE FOR SELECTING OPTIMAL TRANSFORM MATRICES FOR DOWN-SAMPLING DCT IMAGE - Down-sampling of an image may be performed in the DCT domain. Transform matrices are obtained for down-sampling a DCT image of size M×N to a down-sampled DCT image of size I×J. The transform matrices may be used to down-sample the DCT image directly in the DCT domain. A spatial domain down-sampling method is selected and applied to the DCT image to produce a down-sampled DCT reference image. The transform matrices are selected by solving an optimization problem, leading to transform matrices which achieve a desired trade-off between the visual quality of images obtained using the transform matrices and the computational complexity associated with using the transform matrices. The visual quality is a measure of the difference between the down-sampled DCT image obtained using the transform matrices and the visual quality of the DCT reference image obtained using a spatial domain down-sampling method. | 10-18-2012 |
| 20120294511 | EFFICIENT RETRIEVAL OF ANOMALOUS EVENTS WITH PRIORITY LEARNING - Local models learned from anomaly detection are used to rank detected anomalies. The local models include image feature values extracted from an image field of video image data with respect to different predefined spatial and temporal local units, wherein anomaly results are determined by failures to fit to applied anomaly detection module local models. Image features values extracted from the image field local units associated with anomaly results are normalized, and image feature values extracted from the image field local units are clustered. Weights for anomaly results are learned as a function of the relations of the normalized extracted image feature values to the clustered image feature values. The normalized values are multiplied by the learned weights to generate ranking values to rank the anomalies. | 11-22-2012 |
| 20120294512 | LEARNING APPARATUS AND METHOD, IMAGE PROCESSING APPARATUS AND METHOD, PROGRAM, AND RECORDING MEDIUM - There is provided an image processing apparatus including a model-based processing unit that executes model-based processing for converting resolution and converting an image on the basis of a camera model and a predetermined model having aligning, with respect to a high-resolution image output one frame before, and a prediction operation unit that performs a prediction operation on a pixel value of a high-resolution image to be output, on the basis of parameters stored in advance, an observed low-resolution image that is an input low-resolution image, and an image obtained by executing the model-based processing. | 11-22-2012 |
| 20120294513 | IMAGE PROCESSING APPARATUS, IMAGE PROCESSING METHOD, PROGRAM, STORAGE MEDIUM, AND LEARNING APPARATUS - A prediction calculation unit calculates a pixel value of a pixel of interest for each color component by a calculation of a learned predictive coefficient and a predictive tap, and outputs an output image including the pixel value of the pixel of interest of each color component. For example, the present technology can be applied to an image processing apparatus. | 11-22-2012 |
| 20120308121 | IMAGE RANKING BASED ON ATTRIBUTE CORRELATION - Images are retrieved and ranked according to relevance to attributes of a multi-attribute query through training image attribute detectors for different attributes annotated in a training dataset. Pair-wise correlations are learned between pairs of the annotated attributes from the training dataset of images. Image datasets may then be searched via the trained attribute detectors for images comprising attributes in a multi-attribute query, wherein images are retrieved from the searching that each comprise one or more of the query attributes and also in response to information from the trained attribute detectors corresponding to attributes that are not a part of the query but are relevant to the query attributes as a function of the learned plurality of pair-wise correlations. The retrieved images are ranked as a function of respective total numbers of attributes within the query subset attributes. | 12-06-2012 |
| 20120308122 | FAST METHODS OF LEARNING DISTANCE METRIC FOR CLASSIFICATION AND RETRIEVAL - A nearest-neighbor-based distance metric learning process includes applying an exponential-based loss function to provide a smooth objective; and determining an objective and a gradient of both hinge-based and exponential-based loss function in a quadratic time of the number of instances using a computer. | 12-06-2012 |
| 20120328183 | METHOD AND DEVICE FOR SELECTING TRANSFORM MATRICES FOR DOWN-SAMPLING DCT IMAGE USING LEARNING WITH FORGETTING ALGORITHM - Down-sampling of an image may be performed in the DCT domain. A multiple layered network is used to select transform matrices for down-sampling a DCT image of size M×N to a DCT image of size I×J. A spatial domain down-sampling method is selected and applied to the DCT image to produce a down-sampled DCT reference image. A learning with forgetting algorithm is used to apply a decay to the elements of the transform matrix and select a transform matrices which solve an optimization problem. The optimization problem is a function of the visual quality of images obtained using the transform matrices and the computational complexity associated with using the transform matrices. The visual quality is a measure of the difference between the down-sampled DCT image obtained using the transform matrices and the visual quality of the DCT reference image obtained using a spatial domain down-sampling method. | 12-27-2012 |
| 20130011049 | IMAGE PROCESSING APPARATUS, METHOD, AND PROGRAM - The present invention relates to an image processing apparatus, method, and program that can extract an object from an input image more easily and more accurately. | 01-10-2013 |
| 20130077855 | SYSTEMS AND METHODS FOR PROCESSING DOCUMENTS OF UNKNOWN OR UNSPECIFIED FORMAT - A computer implemented method for extracting meaningful text from a document of unknown or unspecified format. In a particular embodiment, the method includes reading the document, thereby to extract raw encoded text, analysing the raw encoded text, thereby to identify one or more text chunks, and for a given chunk, performing compression identification analysis to determine whether compression is likely and, in the event that compression. The method can further include performing a decompression process, performing an encoding identification process thereby to identify a likely character encoding protocol, and converting the chunk using the identified likely character encoding protocol, thereby to output the chunk as readable text. | 03-28-2013 |
| 20130094756 | METHOD AND SYSTEM FOR PERSONALIZED ADVERTISEMENT PUSH BASED ON USER INTEREST LEARNING - Embodiments of the present invention relate to a method and a system for personalized advertisement push based on user interest learning. The method may include: obtaining multiple user interest models through multitask sorting learning; extracting an object of interest in a video according to the user interest models; and extracting multiple visual features of the object of interest, and according to the visual features, retrieving related advertising information in an advertisement database. Through the method and the system provided in embodiments of the present invention, a push advertisement may be closely relevant to the content of the video, thereby meeting personalized requirements of a user to a certain extent and achieving personalized advertisement push. | 04-18-2013 |
| 20130129196 | Image Adjustment - Techniques are disclosed relating to automatically adjusting images. In one embodiment, an image may be automatically adjusted based on a regression model trained with a database of raw and adjusted images. In one embodiment, an image may be automatically adjusted based on a model trained by both a database of raw and adjusted images and a small set of images adjusted by a different user. In one embodiment, an image may be automatically adjusted based on a model trained by a database of raw and adjusted images and predicted differences between a user's adjustment to a small set of images and a predicted adjustment based on the database of raw and adjusted images. | 05-23-2013 |
| 20130129197 | IMAGE RESTORATION BY VECTOR QUANTIZATION UTILIZING VISUAL PATTERNS - The restoration of images by vector quantization utilizing visual patterns is disclosed. One disclosed embodiment comprises restoring detail in a transition region of an unrestored image, by first identifying the transition region and forming blurred visual pattern blocks. These blurred visual pattern blocks are compared to a pre-trained codebook, and a corresponding high-quality visual pattern blocks is obtained. The high-quality visual pattern block is then blended with the unrestored image to form a restored image. | 05-23-2013 |
| 20130236090 | Learning Dictionaries with Clustered Atoms - A dictionary of atoms for coding data is learned by first selecting samples from a set of samples. Similar atoms in the dictionary are clustered, and if a cluster has multiple atoms, the atoms in that cluster are merged into a single atom. The samples can be acquired online. | 09-12-2013 |
| 20130315476 | Automatic Image Adjustment Parameter Correction - Techniques are disclosed relating to modifying an automatically predicted adjustment. In one embodiment, the automatically predicted adjustment may be adjusted, for example, based on a rule. The automatically predicted adjustment may be based on a machine learning prediction. A new image may be globally adjusted based on the modified automatically predicted adjustment. | 11-28-2013 |
| 20130322739 | Image Adjustment - Techniques are disclosed relating to automatically adjusting images. In one embodiment, an image may be automatically adjusted based on a regression model trained with a database of raw and adjusted images. In one embodiment, an image may be automatically adjusted based on a model trained by both a database of raw and adjusted images and a small set of images adjusted by a different user. In one embodiment, an image may be automatically adjusted based on a model trained by a database of raw and adjusted images and predicted differences between a user's adjustment to a small set of images and a predicted adjustment based on the database of raw and adjusted images. | 12-05-2013 |
| 20130343639 | AUTOMATICALLY MORPHING AND MODIFYING HANDWRITTEN TEXT - An automatic handwriting morphing and modification system and method for digitally altering the handwriting of a user while maintaining the overall appearance and style of the user's handwriting. Embodiments of the system and method do not substitute or replace characters or words but instead morph and modify the user's handwritten strokes to retain a visual correlation between the original user's handwriting and the morphed and modified version of the user's handwriting. Embodiments of the system and method input the user's handwriting and a set of morph rules that determine what the handwritten strokes of the user can look more like after processing. Morphs, which are a specific type or appearance of a handwritten stroke, are selected based on the target handwriting. The selected morphs are applied using geometric tuning, semantic tuning, or both. The result is a morphed and modified version of the user's handwriting. | 12-26-2013 |
| 20130343640 | VISION-GUIDED ROBOTS AND METHODS OF TRAINING THEM - Via intuitive interactions with a user, robots may be trained to perform tasks such as visually detecting and identifying physical objects and/or manipulating objects. In some embodiments, training is facilitated by the robot's simulation of task-execution using augmented-reality techniques. | 12-26-2013 |
| 20140010439 | METHOD FOR DETECTING A PREDEFINED SET OF CHARACTERISTIC POINTS OF A FACE - A method of detecting a predefined set of characteristic points of a face from an image of the face includes a step of making the shape and/or the texture of a hierarchy of statistical models of face parts converge over real data supplied by the image of the face. | 01-09-2014 |
| 20140037195 | IMAGE TAG PAIR GRAPH FOR IMAGE ANNOTATION - An approach is described for automatically tagging a single image or multiple images. The approach, in one example embodiment, is based on a graph-based framework that exploits both visual similarity between images and tag correlation within individual images. The problem is formulated in the context of semi-supervised learning, where a graph modeled as a Gaussian Markov Random Field (MRF) is solved by minimizing an objective function (the image tag score function) using an iterative approach. The iterative approach, in one embodiment, comprises: (1) fixing tags and propagating image tag likelihood values from labeled images to unlabeled images, and (2) fixing images and propagating image tag likelihood based on tag correlation. | 02-06-2014 |
| 20140147034 | INFORMATION PROCESSING APPARATUS, CONTROL METHOD THEREFOR, AND ELECTRONIC DEVICE - A technique of high-speed information processing is realized by determining a method of accessing processing target data so as to allow high-speed access in consideration of a memory architecture. According to the technique, in a method of performing information processing by sequentially referring to element data of the processing target data stored in a main memory according to a predetermined information processing rule such as a recognition dictionary, when generating the information processing rule, a reference order of the element data which improves a cache hit rate is determined based on a rule for storing the element data of the processing target data in the main memory, records of the positions of referred element data, and the cache architecture. | 05-29-2014 |
| 20140169662 | Image Retargeting Quality Assessment - A method of performing an image retargeting quality assessment comprising comparing an original image and a retargeted image in a frequency domain, wherein the retargeted image is obtained by performing a retargeting algorithm on the original image. The disclosure also includes an apparatus comprising a processor configured to perform an image retargeting quality assessment, and compare an original image and a retargeted image in a spatial domain, wherein the retargeted image is obtained by performing a retargeting algorithm on the original image, and wherein comparing the original image and the retargeted image in the spatial domain comprises comparing the original image and the retargeted image to determine an amount of shape distortion between the images. | 06-19-2014 |
| 20140219552 | Denoising of Images with Nonstationary Noise - An input image is denoised by first constructing a pixel-wise noise variance map from the input image. The noise has spatially varying variances. The input image is partitioned into patches using the noise variance map. An intermediate image is determined from the patches. Collaborative filtering is applied to each patch in the intermediate image using the noise variance map to produce filtered patches. Then, the filtered patches are projected to an output image. | 08-07-2014 |
| 20140270487 | METHOD AND APPARATUS FOR PROCESSING IMAGE - Provided are a monitoring system and an operating method thereof, and more particularly, an image processing method and apparatus for removing a motion blur of a wide dynamic range (WDR) image by using a machine learning algorithm. The image processing method includes: generating an overlap image by overlapping a first image having a predetermined exposure time and a second image having an exposure time different from that of the first image; detecting a region of interest (ROI) in which a motion blur occurs in the overlap image; and performing a motion blur removing operation of changing an image in the ROI to any one of the first image and the second image by applying a first machine learning algorithm. | 09-18-2014 |
| 20140301634 | DICTIONARY LEARNING DEVICE, PATTERN MATCHING APPARATUS, METHOD FOR LEARNING DICTIONARY AND STORAGE MEDIUM - Provided is a technology which enables further improvement of the accuracy of the determination in the pattern matching processing. | 10-09-2014 |
| 20140314310 | AUTOMATIC ANALYSIS OF RAPPORT - In selected embodiments, one or more wearable mobile devices provide videos and other sensor data of one or more participants in an interaction, such as a customer service or a sales interaction between a company employee and a customer. A computerized system uses machine learning expression classifiers, temporal filters, and a machine learning function approximator to estimate the quality of the interaction. The computerized system may include a recommendation selector configured to select suggestions for improving the current interaction and/or future interactions, based on the quality estimates and the weights of the machine learning approximator. | 10-23-2014 |
| 20150016715 | OUTPUT DEVICE AND OUTPUT SYSTEM - An output device has a first input portion that inputs data of a target state, a second input portion that inputs data of a current state, a sensing portion that senses a state of a shift portion that shifts from the current state to another state including the target state and generates sensing data, a transmission portion that transmits the sensing data, the data of the target state, and the data of the current state, to a predetermined external device, a reception portion that receives from the external device suitability determination result data acquired by determination of suitability of the shift portion configured to shift from the current state to the target state, based on the sensing data, the data of the target state, and the data of the current state, and an output portion that outputs the suitability determination result data that the reception portion has received. | 01-15-2015 |
| 20150086109 | USING MACHINE LEARNING TO DEFINE USER CONTROLS FOR PHOTO ADJUSTMENTS - In various example embodiments, a system and method for using machine learning to define user controls for image adjustment is provided. In example embodiments, a new image to be adjusted is received. A weight is applied to reference images of a reference dataset based on a comparison of content of the new image to the reference image of the reference dataset. A plurality of basis styles is generated by applying weighted averages of adjustment parameters corresponding to the weighted reference images to the new image. Each of the plurality of basis styles comprises a version of the new image with an adjustment of at least one image control based on the weighted averages of the adjustment parameters of the reference dataset. The plurality of basis styles is provided to a user interface of a display device. | 03-26-2015 |
| 20150086110 | PERSON ATTRIBUTE ESTIMATION SYSTEM AND LEARNING-USE DATA GENERATION DEVICE - There is provided a person attribute estimation system capable of accurately estimating an attribute of a person according to an environment in which a person who is the target of attribute estimation is to be captured. The person attribute estimation system includes a camera, an attribute estimation unit for estimating an attribute of a person shown in the image generated by the camera, by using an estimation model, a pseudo-site image generation unit for generating a pseudo-site image by processing data of a standard image which is a person image according to image capturing environment data indicating an image capturing environment of the attribute estimation target person by the camera, and an estimation model relearning unit for performing learning of the estimation model by using the pseudo-site image. | 03-26-2015 |
| 20150125072 | DATA PROCESSING METHOD FOR LEARNING DISCRIMINATOR, AND DATA PROCESSING APPARATUS THEREFOR - A data processing method includes setting a learning data set including a plurality of learning data having respective labels to an uppermost node of a decision tree, setting selection probabilities of the learning data, selecting a combination of the learning data from each of a plurality of sets of learning data assigned to nodes of the decision tree in accordance with the selection probabilities, determining a branch rule for dividing each of the sets of the learning data assigned to the nodes of the decision tree into at least two subsets using the selected combination of the learning data, and assigning the subsets divided in accordance with the branch rule to nodes in a lower level. | 05-07-2015 |
| 20150146972 | PREDICTING A LIGHT PROBE FOR AN OUTDOOR IMAGE - Methods and systems for predicting light probes for outdoor images are disclosed. A light probe database is created to learn a mapping from the outdoor image's features to predicted outdoor light probe illumination parameters. The database includes a plurality of images, image features for each of the plurality of images, and a captured light probe for each of the plurality of images. A light probe illumination model based on a sun model and sky model is fitted to the captured light probes. The light probe for the outdoor image may be predicted based on the database dataset and fitted light probe models. | 05-28-2015 |
| 20150302273 | IMAGE PROCESSING DEVICE, IMAGE PROCESSING METHOD AND MEDIUM - An image processing device according to the present invention includes: a patch generation unit which generates an input patch used for comparison on the basis of an input image; a modification parameter estimation unit which estimates a parameter used in blurred modification on the basis of the input image; a blurred image generation unit which generates a blurred image on the basis of a learning image by using the parameter; a patch pair generation unit which generates a patch pair used to compose a restoration image on the basis of the blurred image and the learning image; a selection unit which selects a patch pair used to compose the restoration image on the basis of the input patch; and a composition unit which composes the restoration image on the basis of the patch pair selected by the selection unit. | 10-22-2015 |
| 20150363670 | IMAGE RECOGNITION METHOD AND CAMERA SYSTEM - A first image taken by a first camera device in the plurality of camera devices and first imaging environment information indicating a first imaging environment of the first camera device at a time of taking the first image is acquired. By using a parameter table that manages imaging environment information indicating an imaging environment at a time of taking an image previously by a camera device and a recognition control parameter indicating a detector corresponding to an imaging environment, a first recognition control parameter indicating a first detector corresponding to third imaging environment that is identical or similar to the first imaging environment indicated by the first imaging environment information acquired from the first camera device is selected from the recognition control parameters. The first image acquired from the first camera device is recognized by using the first detector indicated by the selected first recognition control parameter. | 12-17-2015 |
| 20150363671 | NON-TRANSITORY COMPUTER READABLE MEDIUM, INFORMATION PROCESSING APPARATUS, AND ATTRIBUTE ESTIMATION METHOD - There is provided a non-transitory computer readable medium storing a program causing a computer to execute a process for attribute estimation. The process includes: extracting, for each user, feature quantities of plural pieces of image information that are associated with attributes of the user; integrating the extracted feature quantities for each user; and performing learning, input of the learning being an integrated feature quantity that has been obtained as a result of integration for each user, output of the learning being one attribute, and generating a learning model. | 12-17-2015 |
| 20150379357 | EFFICIENT RETRIEVAL OF ANOMALOUS EVENTS WITH PRIORITY LEARNING - Local models learned from anomaly detection are used to rank detected anomalies. The local models include image feature values extracted from an image field of video image data with respect to different predefined spatial and temporal local units, wherein anomaly results are determined by failures to fit to applied anomaly detection module local models. Image features values extracted from the image field local units associated with anomaly results are normalized, and image feature values extracted from the image field local units are clustered. Weights for anomaly results are learned as a function of the relations of the normalized extracted image feature values to the clustered image feature values. The normalized values are multiplied by the learned weights to generate ranking values to rank the anomalies. | 12-31-2015 |
| 20160004935 | IMAGE PROCESSING APPARATUS AND IMAGE PROCESSING METHOD WHICH LEARN DICTIONARY - An image processing apparatus includes a plurality of dictionaries configured to store a feature of an object and information on an imaging direction in a scene for each kind of imaged scene, a detecting unit configured to detect an object with reference to at least one of the plurality of dictionaries in the scene in which the object has been imaged and which is to be learned, an estimating unit configured to estimate the imaging direction the detected object, a selecting unit configured to select one dictionary from the plurality of dictionaries based on the imaging direction estimated by the estimating unit and the information on the imaging direction in each of the plurality of dictionaries, and a learning unit configured to learn the dictionary selected by the selecting unit, based on a detection result produced by the detecting unit. | 01-07-2016 |
| 20160078312 | IMAGE PROCESSING METHOD AND APPARATUS USING TRAINING DICTIONARY - The image processing method extracts, from a first image, partial areas such that they overlap one another, and provides, by dictionary learning using model images corresponding to multiple types, a set of linear combination approximation bases and a set of classification bases to acquire classification identification values indicating the multiple types to which each partial area belongs. The method approximates the partial areas by linear combination of the linear combination approximation bases to acquire linear combination coefficients, sets the classification identification values by a linear combination of the classification bases and the linear combination coefficients, sets, for each pixel of the first image, one classification identification value from those set for two or more of the partial areas including that pixel, and produces the second image whose each pixel corresponds to that of the first image and has the one classification identification value. | 03-17-2016 |
| 20160078600 | METHOD AND DEVICE FOR PERFORMING SUPER-RESOLUTION ON AN INPUT IMAGE - A method for performing super-resolution on an input image having low resolution, comprises generating a generic training data set of descriptors extracted from regions of training images, and for each patch of the input image, determining a defined number of nearest neighbor regions, extracting example patches from the nearest neighbor regions and collecting the example patches in an example patch data base, determining a combination of low-resolution example patches that, according to their descriptors, optimally approximate the current patch, and constructing a high-resolution patch, wherein a super-resolved image is obtained. | 03-17-2016 |
| 20160104049 | Lateral Sign Placement Determination - Systems, methods, and apparatuses are described for predicting the placement of road signs. A device receives data depicting road signs from multiple vehicles. The device analyzes a detected placement of the road signs and at least one characteristic of a collection of the data. The characteristic describes the road upon which the data was collected, an operation of the vehicle from which the data was collected, or an environment in which the data was collected. The device generates a model that associates values for the detected placement of the road signs with values for the at least one characteristic. The model may be later accessed to interpret subsequent sets of data describing one or more road signs. | 04-14-2016 |
| 20160124996 | IMAGE RANKING BASED ON ATTRIBUTE CORRELATION - Images are retrieved and ranked according to relevance to attributes of a multi-attribute query through training image attribute detectors for different attributes annotated in a training dataset. Pair-wise correlations are learned between pairs of the annotated attributes from the training dataset of images. Image datasets may are searched via the trained attribute detectors for images comprising attributes in a multi-attribute query. The retrieved images are ranked as a function of comprising attributes that are not within the query subset plurality of attributes but are paired to one of the query subset plurality of attributes by the pair-wise correlations, wherein the ranking is an order of likelihood that the different ones of the attributes will appear in an image with the paired one of the query subset plurality of attributes. | 05-05-2016 |
| 20160125271 | FEATURE AMOUNT CONVERSION APPARATUS, LEARNING APPARATUS, RECOGNITION APPARATUS, AND FEATURE AMOUNT CONVERSION PROGRAM PRODUCT - A feature amount conversion apparatus includes a plurality of bit rearrangement units, a plurality of logical operation units, and a feature integration unit. The bit rearrangement units generate rearranged bit strings by rearranging elements of an inputted binary feature vector into diverse arrangements. The logical operation units generate logically-operated bit strings by performing a logical operation on the inputted feature vector and each of the rearranged bit strings. The feature integration unit generates a nonlinearly converted feature vector by integrating the generated logically-operated bit strings. | 05-05-2016 |
| 20160180502 | Method for upscaling an image and apparatus for upscaling an image | 06-23-2016 |
| 20160189003 | SIMILAR ITEM DETECTION - A method to determine image similarities. The method may include obtaining a first image and a second image and determining a discrete transform difference between a first discrete transform of the first image and a second discrete transform of the second image. The method may also include determining multiple first intensity vectors for the first image and determining multiple second intensity vectors for the second image. The method may also include determining an intensity vector difference between the multiple first intensity vectors and the multiple second intensity vectors and determining a color difference between a first color histogram of the first image and a second color histogram of the second image. The method may also include determining a similarity between the first image and the second image based on the discrete transform difference, the intensity vector difference, and the color difference. | 06-30-2016 |
| 20160189011 | COMPLEMENTARY ITEM RECOMMENDATIONS USING IMAGE FEATURE DATA - An apparatus and method to facilitate finding complementary recommendations are disclosed herein. One or more fashion trend or pleasing color combination rules are determined based on data obtained from one or more sources. One or more template images and rule triggers corresponding to the fashion trend or pleasing color combination rules are generated, each of the rule triggers associated with at least one of the template images. A processor compares a first image attribute of a particular one of the template images to a second image attribute of each of a plurality of inventory images corresponding to the plurality of inventory items to identify the inventory items complementary to the query image. The particular one of the template images is selected based on the rule trigger corresponding to the particular one of the template images being applicable for a query image. | 06-30-2016 |
| 20190147320 | "Matching Adversarial Networks" | 05-16-2019 |
