Patent application number | Description | Published |
20100034464 | APPARATUS AND METHOD FOR TRACKING IMAGE - An image processing apparatus includes a classification unit configured to extract N features from an input image using pre-generated N feature extraction units and calculate confidence value which represents object-likelihood based on the extracted N features, an object detection unit configured to detect an object included in the input image based on the confidence value, a feature selection unit configured to select M feature extraction units from the N feature extraction units such that separability between the confidence value of the object and that of background thereof becomes greater than a case where the N feature extraction units are used, the M being a positive integer smaller than N, and an object tracking unit configured to extract M features from the input image and tracks the object using the M features selected by the feature selection unit. | 02-11-2010 |
20140016831 | APPARATUS FOR RETRIEVING INFORMATION ABOUT A PERSON AND AN APPARATUS FOR COLLECTING ATTRIBUTES - A first acquisition unit is configured to acquire the image including a plurality of frames. A first extraction unit is configured to extract a plurality of persons from the frames, and to extract a plurality of first attributes from each of the persons. The first attributes feature each person. A second extraction unit is configured to extract a plurality of second attributes from a first person indicated by a user. The second attributes feature the first person. A retrieval unit is configured to retrieve information about a person similar to the first person from the persons, based on at least one of the second attributes as a retrieval condition. An addition unit is configured to, when at least one of the first attributes of a retrieved person by the retrieval unit is different from the second attributes, add the at least one of the first attributes to the retrieval condition. | 01-16-2014 |
20160088261 | SYSTEM AND A METHOD FOR SPECIFYING AN IMAGE CAPTURING UNIT, AND A NON-TRANSITORY COMPUTER READABLE MEDIUM THEREOF - According to one embodiment, a system includes a portable device, a plurality of second image capturing units, an extraction unit, a calculation unit, and a specifying unit. The portable device includes a first image capturing unit that captures a first image of a person, and a sending unit that sends the first image. The plurality of second image capturing units captures second images. The extraction unit extracts a first feature of the first image and a second feature of each of the second images. The calculation unit calculates a similarity based on the first feature and the second feature of the each of the second images. If the similarity for a second image is larger than a predetermined threshold, the specifying unit specifies a second image capturing unit that has captured the second image, among the plurality of second image capturing units. | 03-24-2016 |
Patent application number | Description | Published |
20090262989 | IMAGE PROCESSING APPARATUS AND METHOD - An image processing apparatus includes an image input unit, a feature point extraction unit which extracts a plurality of feature points from an input image, a three-dimensional model storage unit which stores a three-dimensional model and reference feature point coordinates on the three-dimensional model, a target area setting unit which sets target areas from the three-dimensional model, a correspondence relationship calculation unit which, using the extracted feature points and reference feature points belonging to the target areas, estimates a correspondence relationship between the input image and the target areas, and a three-dimensional model integration unit which integrates target areas related to the image. | 10-22-2009 |
20120027292 | THREE-DIMENSIONAL OBJECT DETERMINING APPARATUS, METHOD, AND COMPUTER PROGRAM PRODUCT - According to one embodiment, a three-dimensional object determining apparatus includes: a detecting unit configured to detect a plurality of feature points of an object included in an image data that is acquired; a pattern normalizing unit configured to generate a normalized pattern that is normalized by a three-dimensional model from the image data using the plurality of feature points; an estimating unit configured to estimate an illumination direction in which light is emitted to the object in the image data from the three-dimensional model and the normalized pattern; and a determining unit configured to determine whether or not the object in the image data is a three-dimensional object on the basis of the illumination direction. | 02-02-2012 |
20120243779 | RECOGNITION DEVICE, RECOGNITION METHOD, AND COMPUTER PROGRAM PRODUCT - According to an embodiment, a recognition device includes a generation unit to select, plural times, groups each including learning samples from a storage unit, learn a classification metric for classifying the groups selected in each selection, and generate an evaluation metric including the classification metrics; a transformation unit to transform a first feature value of an image including an object into a second feature value using the evaluation metric; a calculation unit to calculate similarities of the object to categories in a table using the second feature value and reference feature values; and a registration unit to register the second feature value as the reference feature value in the table associated with the category of the object and register the first feature value as the learning sample belonging to the category of the object in the storage unit. The generation unit performs the generation again. | 09-27-2012 |
20120246099 | LEARNING DEVICE, LEARNING METHOD, AND COMPUTER PROGRAM PRODUCT - According to an embodiment, a learning device includes a selecting unit, a learning unit, and an evaluating unit. The selecting unit performs a plurality of selection processes of selecting a plurality of groups including one or more learning samples from a learning sample storage unit, where respective learning samples are classified into any one of a plurality of categories. The learning unit learns a classification metric and obtains a set of a classification metric. The evaluating unit acquires two or more evaluation samples of different categories from an evaluation sample storage unit where respective evaluation samples are classified into any one of a plurality of categories; evaluates the classification metric included in the set of the classification metric using the two or more acquired evaluation samples; acquires a plurality of classification metric corresponding to the evaluation results from the set of the classification metric; and thereby generates an evaluation metric including the plurality of classification metric. | 09-27-2012 |
20130243271 | COLLATION APPARATUS, COLLATION METHOD, AND COMPUTER PROGRAM PRODUCT - According to an embodiment, a collation apparatus includes a receiving unit, a detecting unit, a setting unit, a face collation unit, an object collation unit, and a calculating unit. The receiving unit is configured to receive a captured image including a user's face and an object positioned with respect to the face. The detecting unit is configured to detect a face region from the image. The setting unit is configured to set an object region in the image. The face collation unit is configured to collate a face feature vector extracted from the face region with a stored face feature vector. The object collation unit is configured to collate an object feature vector extracted from the object region with a stored object feature vector. The calculating unit is configured to calculate a user collation using at least one of the collation results for the face and object feature vectors. | 09-19-2013 |
20140139663 | WIRELESS COMMUNICATION DEVICE, WIRELESS COMMUNICATION METHOD, AND COMPUTER PROGRAM PRODUCT - According to an embodiment, a wireless communication device includes a detector to detect a mobile object by referring to sensing information; a first communicating unit to communicate mobile object information, which is related to a detection result of the mobile object, with another wireless communication device; a first calculator to calculate a moving path of the mobile object between wireless communication devices by referring to the detection result of the mobile object and mobile object information received from the other wireless communication device; a second communicating unit to communicate movement information, which is related to the moving path of the mobile object, with the other wireless communication device; and a second calculator to calculate distances between wireless communication devices that are dependent on the number of times of movement in the moving path by referring to the calculated moving path and movement information received from the other wireless communication device. | 05-22-2014 |
20140141823 | COMMUNICATION DEVICE, COMUNICATION METHOD AND COMPUTER PROGRAM PRODUCT - According to an embodiment, a communication device includes an analyzer, a switching unit and a communication unit. The analyzer is configured to analyze an image taken at a periphery of the communication device. The switching unit is configured to switch a communication counterpart from a first communication device to a second communication device based on an analysis result of the image. The communication unit is configured to communicate with the second communication device after switching. | 05-22-2014 |
20140219518 | ESTIMATING APPARATUS, METHOD THEREOF, AND COMPUTER PROGRAM PRODUCT THEREFOR - An estimating apparatus configured to estimate a correct attribute value is provided. The estimating apparatus extracts feature quantities from an image including a person, calculates a first likelihood of the feature quantity for respective attribute classes; calculating second likelihoods for the respective attribute classes from the first likelihoods for the respective attribute classes; specifies the attribute class having the highest second likelihood; calculates an estimated attribute value of the specific attribute class and estimated attribute values of selected classes by using the feature quantity; and applies the second likelihood on the estimated attribute value of the specific attribute class as a weight, applies the second likelihoods on the estimated attribute values of the selected classes as a weight and add the same, and calculates a corrected attribute value of the specific attribute class. | 08-07-2014 |
20140219554 | PATTERN RECOGNITION APPARATUS, METHOD THEREOF, AND PROGRAM PRODUCT THEREFOR - When a feature vector is converted to a reduced vector, a converting unit samples N components of interest from the M components of the feature vector, executes the process of calculating one component of the reduced vector from the N components of interest by d times to create the d-dimensional reduced vector and, the converting unit (1) excludes the components within a predetermined distance D in the same row as the previous component of interest sampled at the previous sampling, (2) excludes the components in the same column as the previous component of interest including the component k rows apart and within the distance (D−k) from the component k rows apart, and (3) samples the component of interest of this time from the remaining components after exclusion when sampling the component of interest. | 08-07-2014 |
Patent application number | Description | Published |
20090110303 | OBJECT RECOGNIZING APPARATUS AND METHOD - An object is identified by detecting an object area image of an object to be recognized from a degraded image, converting the object area image to a frequency area, extracting a feature vector which indicates the amount of blur, comparing the feature vector and a classified plurality of blurred images, obtaining a cluster which is the most similar to the feature vector, selecting one point spread function corresponding to the similar cluster, restoring the object area image to the image before being blurred using the point spread function, and comparing the restored image and a target image. | 04-30-2009 |
20090136137 | IMAGE PROCESSING APPARATUS AND METHOD THEREOF - The invention includes a reference oint setting unit configured to extract a plurality of reference points from an input image; a pattern extractor configured to extract a local pattern of the reference points; a characteristic set holder configured to hold a group of characteristic sets having both local patterns of the reference points extracted from a learned image and vectors from the reference points to characteristic points to be detected; a matching unit configured to compare the local patterns extracted from the reference points and the group of characteristic sets and select the nearest characteristic set as a characteristic set having the most similar pattern; and a characteristic point detector configured to detect a final position of the characteristic point based on a vector from the reference point to the characteristic point included in the selected nearest characteristic set. | 05-28-2009 |
20160086057 | FEATURE POINT DETECTION DEVICE, FEATURE POINT DETECTION METHOD, AND COMPUTER PROGRAM PRODUCT - According to an embodiment, a feature point detection device includes a generator to generate a K-class classifier and perform, for T times, an operation in which a first displacement vector is obtained that approximates D number of initial feature points of each training sample classified on a class-by-class basis to true feature points; a calculator to calculate, from the first displacement vectors, second displacement label vectors each unique to one second displacement vector, and a second displacement coordinate vector common to the second displacement vectors; a classifier to apply the K-class classifiers to the input image and obtain a second displacement label vector associated with a class identifier output from each K-class classifier; an adder to add up the second displacement label vectors; and a detector to detect D number of true feature points based on the initial feature points, the added label vector, and the second displacement coordinate vector. | 03-24-2016 |
Patent application number | Description | Published |
20140139690 | INFORMATION PROCESSING APPARATUS, CAMERA HAVING COMMUNICATION FUNCTION, AND INFORMATION PROCESSING METHOD - An information processing apparatus has a communication part, a message receiving part, a network-information acquiring part, a peripheral-apparatus information managing part, a task accepting part, a task allocating part, a task processing part, a process-related information generating part, and a message transmitting part configured to generate a message that includes the process-related information and transmit the message including the process-related information to the other communication apparatuses via the communication part and the network. | 05-22-2014 |
20150181170 | INFORMATION ASSOCIATING APPARATUS, METHOD THEREOF AND PROGRAM THEREFOR - According to one embodiment, an information associating apparatus includes an acquisition unit configured to acquire an acquisition image taken by a camera and individual identification information of the camera, an analysis unit configured to analyze attribute information of the camera from an attribute information expression body shown in the acquisition image, a detection unit configured to detect an pattern representing a specific direction recorded in the acquisition image and an association unit configured to form a pair by associating the individual identification information and the attribute information based on a detection result concerning the specific direction calculated from the pattern. | 06-25-2015 |
20150269437 | IMAGE PROCESSING APPARATUS, METHOD THEREOF AND PROGRAM THEREFOR - An image processing method includes: retaining marker information including markers, each of the markers having a type which is shape, pattern or color; acquiring images in which at least one of the markers is caught; referring the marker information to detect the type and a position of the marker caught in the image; and dividing the image into a plurality of divided areas on the basis of the positions of one or more markers in the image, the plurality of divided areas having no common area and each including at least one type of the marker. | 09-24-2015 |