Patent application number | Description | Published |
20090074252 | REAL-TIME SELF COLLISION AND OBSTACLE AVOIDANCE - A system, method, and computer program product for avoiding collision of a body segment with unconnected structures in an articulated system are described. A virtual surface is constructed surrounding an actual surface of the body segment. Distances between the body segment and unconnected structures are monitored. Responding to an unconnected structure penetrating the virtual surface, a redirected joint motion that prevents the unconnected structure from penetrating deeper into the virtual surface is determined. The body segment is redirected based on the redirected joint motion to avoid colliding with the unconnected structure. | 03-19-2009 |
20090118863 | REAL-TIME SELF COLLISION AND OBSTACLE AVOIDANCE USING WEIGHTING MATRIX - A system, method, and computer program product for avoiding collision of a body segment with other structures in an articulated system are described. According to one aspect, a collision function is determined for avoiding such collision. A distance between the body segment and one such structure is measured. A weighting matrix is generated based on the collision function and the distance, and used to determine a redirected motion for the body segment. The body segment is redirected based on the redirected motion to avoid colliding with the structure. | 05-07-2009 |
20090175540 | Controlled human pose estimation from depth image streams - A system, method, and computer program product for estimating upper body human pose are described. According to one aspect, a plurality of anatomical features are detected in a depth image of the human actor. The method detects a head, neck, and torso (H-N-T) template in the depth image, and detects the features in the depth image based on the H-N-T template. An estimated pose of a human model is estimated based on the detected features and kinematic constraints of the human model. | 07-09-2009 |
20090252423 | Controlled human pose estimation from depth image streams - A system, method, and computer program product for estimating human body pose are described. According to one aspect, anatomical features are detected in a depth image of a human actor. The method detects a head, neck, and trunk (H-N-T) template in the depth image, and detects limbs in the depth image based on the H-N-T template. The anatomical features are detected based on the H-N-T template and the limbs. An estimated pose of a human model is estimated based on the detected features and kinematic constraints of the human model. | 10-08-2009 |
20100215257 | CAPTURING AND RECOGNIZING HAND POSTURES USING INNER DISTANCE SHAPE CONTEXTS - A system, method, and computer program product for recognizing hand postures are described. According to one aspect, a set of training images is provided with labels identifying hand states captured in the training images. Inner Distance Shape Context (IDSC) descriptors are determined for the hand regions in the training images, and fed into a Support Vector Machine (SVM) classifier to train it to classify hand shapes into posture classes. An IDSC descriptor is determined for a hand region in a testing image, and classified by the SVM classifier into one of the posture classes the SVM classifier was trained for. The hand posture captured in the testing image is recognized based on the classification. | 08-26-2010 |
20100215271 | BODY FEATURE DETECTION AND HUMAN POSE ESTIMATION USING INNER DISTANCE SHAPE CONTEXTS - A system, method, and computer program product for estimating human body pose are described. According to one aspect, a human figure silhouette is segmented from a depth image of a human actor. Contour points are sampled along the human figure silhouette. Inner Distance Shape Context (IDSC) descriptors of the sample contour points are determined and compared to IDSC descriptors of the feature points in an IDSC gallery for similarity. For each of the feature points, the sample contour point with the IDSC descriptor that is most similar to an IDSC of the feature point is identified as that feature point in the depth image. An estimated pose of a human model is estimated based on the detected feature points and kinematic constraints of the human model. | 08-26-2010 |
20110054870 | Vision Based Human Activity Recognition and Monitoring System for Guided Virtual Rehabilitation - A system, method, and computer program product for providing a user with a virtual environment in which the user can perform guided activities and receive feedback are described. The user is provided with guidance to perform certain movements. The user's movements are captured in an image stream. The image stream is analyzed to estimate the user's movements, which is tracked by a user-specific human model. Biomechanical quantities such as center of pressure and muscle forces are calculated based on the tracked movements. Feedback such as the biomechanical quantities and differences between the guided movements and the captured actual movements are provided to the user. | 03-03-2011 |
20110066283 | WHOLE-BODY HUMANOID CONTROL FROM UPPER-BODY TASK SPECIFICATIONS - A system, method, and computer program product for generating dynamically feasible whole-body motion of a humanoid robot while realizing specified upper-body task motion are described. A kinematically feasible upper-body motion is generated based on the specified upper-body motion. A series of zero-moment points (ZMP) are computed for the generated motion and used to determine whether such motion is dynamically feasible. If the motion is not dynamically feasible, then the torso acceleration is modified to make the motion dynamically feasible, and otherwise synchronized as needed. A series of modified ZMP is determined based on the modified torso acceleration and used to distribute the resultant net ground reaction force and moment to the two feet. | 03-17-2011 |