Patent application number | Description | Published |
20090292549 | SOCIAL NETWORK CONSTRUCTION BASED ON DATA ASSOCIATION - A system for social network construction. Video analytics and association may be used to develop a social network. Also, social groups may be developed from temporal proximity of persons. In the case of several social networks, they may be collapsed into one network or a weighted graph that mining algorithms can handle. | 11-26-2009 |
20110216964 | META-CLASSIFIER SYSTEM FOR VIDEO ANALYTICS - A system for meta-classification having a training phase mechanism and an operational phase mechanism. The training phase mechanism may have a detection and tracking module, a classifier section connected to the detection and tracking module, a feature synthesis module connected to the classifier section, a labeling module connected to the feature synthesis module and a training data module connected to the labeling module. The operational phase mechanism may have a detection and tracking module, a classifier section connected to the detection and tracking module, a feature synthesis module connected to the classifier section and a meta-classification module connected to the feature synthesis module and the training module. The training phase mechanism may provide parameters and settings to the operational phase mechanism. | 09-08-2011 |
20120078510 | CAMERA AND INERTIAL MEASUREMENT UNIT INTEGRATION WITH NAVIGATION DATA FEEDBACK FOR FEATURE TRACKING - A navigation device is provided herein comprising an inertial measurement unit (IMU), a camera, and a processor. The IMU provides an inertial measurement to the processor and the camera provides at least one image frame to the processor. The processor is configured to determine navigation data based on the inertial measurement and the at least one image frame, wherein at least one feature is extracted from the at least one image frame based on the navigation data. | 03-29-2012 |
20120089330 | SYSTEM AND METHOD FOR WAVELET-BASED GAIT CLASSIFICATION - A motion classification system comprises an inertial measurement unit configured to sense motion of a user and to output one or more channels of inertial motion data corresponding to the sensed motion; and a processing unit configured to calculate a coefficient vector for each of the one or more channels based on a wavelet transformation of the respective inertial motion data, and to select one of a plurality of gaits as the user's gait based on the calculated coefficient vector of at least one of the one or more channels and on a plurality of templates, each template corresponding to one of the plurality of gaits. | 04-12-2012 |
20120130284 | SYSTEM AND METHOD FOR CONSTRUCTING DISTANCE ESTIMATE MODELS FOR PERSONAL NAVIGATION - Systems and methods for constructing distance estimate models for personal navigation are provided. In one embodiment, a distance estimation system comprises: a gait information memory configured to store gait information about a gait mode; a biometric data memory configured to store a biometric profile for a user; a frequency module configured to identify a gait frequency; and a distance calculation module configured to calculate the distance traveled by the user by creating a distance estimate model based on the gait mode, the biometric profile, and the gait frequency, wherein the distance calculation module creates the distance estimate model by performing a regression analysis on movement information from at least one user. | 05-24-2012 |
20120150441 | SYSTEMS AND METHODS FOR NAVIGATION USING CROSS CORRELATION ON EVIDENCE GRIDS - Systems and methods for navigation using cross correlation on evidence grids are provided. In one embodiment, a system for using cross-correlated evidence grids to acquire navigation information comprises: a navigation processor coupled to an inertial measurement unit, the navigation processor configured to generate a navigation solution; a sensor configured to scan an environment; an evidence grid creator coupled to the sensor and the navigation processor, wherein the evidence grid creator is configured to generate a current evidence grid based on data received from the sensor and the navigation solution; a correlator configured to correlate the current evidence grid against a historical evidence grid stored in a memory to produce displacement information; and where the navigation processor receives correction data derived from correlation of evidence grids and adjusts the navigation solution based on the correction data. | 06-14-2012 |
20120243775 | WIDE BASELINE FEATURE MATCHING USING COLLOBRATIVE NAVIGATION AND DIGITAL TERRAIN ELEVATION DATA CONSTRAINTS - A method for wide baseline feature matching comprises capturing one or more images from an image sensor on each of two or more platforms when the image sensors have overlapping fields of view, performing a 2-D feature extraction on each of the captured images in each platform using local 2-D image feature descriptors, and calculating 3-D feature locations on the ellipsoid of the Earth surface from the extracted features using a position and attitude of the platform and a model of the image sensor. The 3-D feature locations are updated using digital terrain elevation data (DTED) as a constraint, and the extracted features are matched using the updated 3-D feature locations to create a common feature zone. A subset of features from the common feature zone is selected, and the subset of features is inputted into a collaborative filter in each platform. A convergence test is then performed on other subsets in the common feature zone, and falsely matched features are pruned from the common feature zone. | 09-27-2012 |
20120245844 | COLLABORATIVE NAVIGATION USING CONDITIONAL UPDATES - A method for collaborative navigation between two or more platforms is provided. The method comprises establishing a communication link between a first platform and a second platform, making a sensor measurement from the first platform, updating state and covariance elements of the first platform, and transmitting the updated state and covariance elements from the first platform to the second platform. A conditional update is performed on the second platform to compute a new estimate of state and covariance elements on the second platform, which takes into account the measurement from the first platform. The method further comprises making a sensor measurement from the second platform, updating state and covariance elements of the second platform, and transmitting the updated state and covariance elements from the second platform to the first platform. A conditional update is performed on the first platform to compute a new estimate of state and covariance elements on the first platform, which takes into account the measurement from the second platform. | 09-27-2012 |
20130022233 | IDENTIFYING TRUE FEATURE MATCHES FOR VISION BASED NAVIGATION - An example embodiment includes a method for identifying true feature matches from a plurality of candidate feature matches for vision based navigation. A weight for each of the plurality of candidate feature matches can be set. The method also includes iteratively performing for N iterations: calculating a fundamental matrix for the plurality of candidate feature matches using a weighted estimation that accounts for the weight of each of the plurality of candidate feature matches; calculating a distance from the fundamental matrix for each of the plurality of candidate feature matches; and updating the weight for each of the plurality of candidate feature matches as a function of the distance for the respective candidate feature match. After N iterations candidate feature matches having a distance less than a distance threshold can be selected as true feature matches | 01-24-2013 |
20130080045 | GENERIC SURFACE FEATURE EXTRACTION FROM A SET OF RANGE DATA - An example embodiment includes a method including receiving a three-dimensional set of range data including a plurality of points from one or more range finders. The method also includes extracting one or more surface features. Extracting includes segmenting the set of range data into a plurality of surfaces based on one or more edges, selecting one or more of the plurality of surfaces as the one or more surface features, and describing the one or more surface features based on a generic descriptor that can describe both planar and non-planar surface features. | 03-28-2013 |
20130131984 | RAPID LIDAR IMAGE CORRELATION FOR GROUND NAVIGATION - A method includes generating current coarse edge count representation based on current fine grid representation of current section, correlating current edge quantity values of current coarse pixels with historical edge quantity values of historical coarse pixels of historical coarse edge count representation of environment, and identifying first subsection of historical coarse edge count representation with highest correlation to current coarse edge count representation. Each current coarse pixel in current coarse edge count representation represents current fine pixels from current fine grid representation. Fine grid representation of current section of environment is based on data from range and attitude sensor. Each current coarse pixel within current coarse edge count representation includes current edge quantity value that represents quantity of current fine pixels represented by current coarse pixel that include edge. Each historical coarse pixel corresponds to historical fine pixels in historical fine grid representation of environment. | 05-23-2013 |
20130179112 | ROBUST METHOD FOR SIGNAL SEGMENTATION FOR MOTION CLASSIFICATION IN PERSONAL NAVIGATION - A method to accurately detect true peaks and true valleys in a real-time incoming signal is provided. The method includes segmenting the real-time incoming signal into short-time intervals; determining an initial estimated frequency by fast Fourier transforming data in the short-time intervals, setting a sliding window width based on the initial estimated frequency, determining at least one peak data element or valley data element based on analysis of the real-time incoming signal within a first sliding window; and determining at least one peak data element or valley data element based on analysis of the real-time incoming signal within a second sliding window. A first portion of the second sliding window overlaps a second portion of the first sliding window. | 07-11-2013 |
20130304383 | SYSTEMS AND METHODS FOR LANDMARK SELECTION FOR NAVIGATION - Systems and methods are provided for selecting landmarks for navigation. In one embodiment, a system comprises an IMU that provides inertial measurements for a vehicle and at least one image sensor that acquires measurements of the vehicle's environment. The system also comprises a processing unit that calculates a navigation solution for the vehicle based on the inertial measurements, identifies a plurality of landmarks in the acquired measurements, and identifies a plurality of usable landmarks from the plurality of landmarks. The processing unit also selects a subset of useable landmarks from the plurality of useable landmarks such that the subset of landmarks has a smaller dilution of precision (DOP) than other possible subsets of landmarks from the plurality of useable landmarks, and calculates an updated navigation solution from the subset of landmarks. The DOP is an amplification factor of measurement errors derived from the geometry of the subset of useable landmarks. | 11-14-2013 |
20140022262 | METHOD OF CORRELATING IMAGES WITH TERRAIN ELEVATION MAPS FOR NAVIGATION - A method for navigation comprises constructing a current map that includes two-dimensional or three dimensional representations of an area, detecting one or more edge features on the current map, and generating a first fine-edge map based on the edge features. The method further comprises retrieving a historical map that includes two-dimensional or three dimensional representations of the area, detecting one or more edge features on the historical map, and generating a second fine-edge map based on the edge features. Thereafter, a coarse version of the current map is generated from the first fine-edge map, and a coarse version of the historical map is generated from the second fine-edge map. The coarse versions of the current and historical maps are then correlated to determine a first position and orientation. The first fine-edge map is then correlated with the second fine-edge map to determine a second, more accurate, position and orientation. | 01-23-2014 |
20140025331 | SYSTEMS AND METHODS FOR CORRELATING REDUCED EVIDENCE GRIDS - A system is provided for correlating evidence grids. In certain embodiments, the system includes a sensor that generates signals describing a current section of an environment; a memory configured to store measurements of historical sections of the environment; and a processor coupled to the sensor and configured to calculate navigation parameters based on signals received from the sensor. Further, the processor converts the signals received from the sensor into a current evidence grid and removes data from the current evidence grid to form a reduced evidence grid; converts the measurements of historical sections into a historical evidence grid; and correlates the reduced evidence grid with the historical evidence grid by adjusting position and orientation of the reduced evidence grid and the historical evidence grid in relation to one another and calculating correlative values, and searching for a highest correlative value. | 01-23-2014 |
20140153788 | SYSTEM AND METHODS FOR FEATURE SELECTION AND MATCHING - Systems and methods for feature selection and matching are provided. In certain embodiments, a method for matching features comprises extracting a first plurality of features from current image data acquired from at least one sensor and extracting a second plurality of features from a prior map, wherein the prior map represents an environment containing the navigation system independently of data currently acquired by the at least one sensor. The method also comprises identifying at least one first feature in the first plurality of features and at least one second feature in the second plurality of features that have associated two-dimensional representations; and identifying at least one corresponding pair of features by comparing a three-dimensional representations of the at least one first feature to a three-dimensional representation of the at least one second feature. | 06-05-2014 |
20140204081 | SYSTEMS AND METHODS FOR 3D DATA BASED NAVIGATION USING DESCRIPTOR VECTORS - Systems and methods for 3D data based navigation using descriptor vectors are provided. In at least one embodiment, a method for identifying corresponding segments in different frames of data comprises identifying a first segment set in a first frame in multiple frames acquired by at least one sensor, and identifying a second segment set in a second frame in the multiple frames. The method also comprises calculating a first and second set of descriptor vectors, wherein the first and second sets of descriptor vectors comprise a descriptor vector for each segment in the respective first and second segment set, wherein a descriptor vector describes an indexed plurality of characteristics; and identifying corresponding segments by comparing the first set of descriptor vectors against the second set of descriptor vectors, wherein the corresponding segments describe characteristics of the same feature in the environment. | 07-24-2014 |
20140204082 | SYSTEMS AND METHODS FOR 3D DATA BASED NAVIGATION USING A WATERSHED METHOD - Systems and methods for 3D data based navigation using a watershed method are provided. In at least one embodiment, a method for segmenting three-dimensional frames of data comprises acquiring at least one frame from at least one sensor, wherein the at least one frame provides a three-dimensional description of an environment containing the at least one sensor; and identifying a surface in the at least one frame. The method further comprises computing at least one residual map for the at least one frame based on the orthogonal distance from data points on the surface to at least one polynomial surface fitted to the surface; and segmenting the at least one residual map by performing a watershed algorithm on the residual map. | 07-24-2014 |
20140379179 | SYSTEMS AND METHODS FOR AUTONOMOUS LANDING USING A THREE DIMENSIONAL EVIDENCE GRID - A method for autonomous landing of an unmanned aerial vehicle (UAV) comprising: obtaining sensor data corresponding to one or more objects outside of the aircraft using at least one onboard sensor; using the sensor data to create a three dimensional evidence grid, wherein a three dimensional evidence grid is a three dimensional world model based on the sensor data; combining a priori data with the three dimensional evidence grid; locating a landing zone based on the combined three dimensional evidence grid and a priori data; validating an open spots in the landing zone, wherein validating includes performing surface condition assessment of a surface of the open spots; generating landing zone motion characterization, wherein landing zone motion characterization includes characterizing real time landing zone pitching, heaving, rolling or forward motion; processing the three dimensional evidence grid data to generate flight controls to land the aircraft in one of the open spots; and controlling the aircraft according to the flight controls to land the aircraft. | 12-25-2014 |
20150073707 | SYSTEMS AND METHODS FOR COMPARING RANGE DATA WITH EVIDENCE GRIDS - Systems and methods for comparing range data with evidence grids are provided. In certain embodiments, a system comprises an inertial measurement unit configured to provide inertial measurements; and a sensor configured to provide range detections based on scans of an environment containing the navigation system. The system further comprises a navigation processor configured to provide a navigation solution, wherein the navigation processor is coupled to receive the inertial measurements from the inertial measurement unit and the range measurements from the sensor, wherein computer readable instructions direct the navigation processor to identify a portion of an evidence grid based on the navigation solution; compare the range detections with the portion of the evidence grid; and calculate adjustments to the navigation solution based on the comparison of the range detections with the portion of the evidence grid to compensate for errors in the inertial measurement unit. | 03-12-2015 |