Patent application number | Description | Published |
20110085705 | DETECTION OF BODY AND PROPS - A system and method for detecting and tracking targets including body parts and props is described. In one aspect, the disclosed technology acquires one or more depth images, generates one or more classification maps associated with one or more body parts and one or more props, tracks the one or more body parts using a skeletal tracking system, tracks the one or more props using a prop tracking system, and reports metrics regarding the one or more body parts and the one or more props. In some embodiments, feedback may occur between the skeletal tracking system and the prop tracking system. | 04-14-2011 |
20110210915 | Human Body Pose Estimation - Techniques for human body pose estimation are disclosed herein. Images such as depth images, silhouette images, or volumetric images may be generated and pixels or voxels of the images may be identified. The techniques may process the pixels or voxels to determine a probability that each pixel or voxel is associated with a segment of a body captured in the image or to determine a three-dimensional representation for each pixel or voxel that is associated with a location on a canonical body. These probabilities or three-dimensional representations may then be utilized along with the images to construct a posed model of the body captured in the image. | 09-01-2011 |
20120087575 | RECOGNIZING HAND POSES AND/OR OBJECT CLASSES - There is a need to provide simple, accurate, fast and computationally inexpensive methods of object and hand pose recognition for many applications. For example, to enable a user to make use of his or her hands to drive an application either displayed on a tablet screen or projected onto a table top. There is also a need to be able to discriminate accurately between events when a user's hand or digit touches such a display from events when a user's hand or digit hovers just above that display. A random decision forest is trained to enable recognition of hand poses and objects and optionally also whether those hand poses are touching or not touching a display surface. The random decision forest uses image features such as appearance, shape and optionally stereo image features. In some cases, the training process is cost aware. The resulting recognition system is operable in real-time. | 04-12-2012 |
20120162354 | Remote Workspace Sharing - Existing remote workspace sharing systems are difficult to use. For example, changes made on a common work product by one user often appear abruptly on displays viewed by remote users. As a result the interaction is perceived as unnatural by the users and is often inefficient. Images of a display of a common work product are received from a camera at a first location. These images may also comprise information about objects between the display and the camera such as a user's hand editing a document on a tablet PC. These images are combined with images of the shared work product and displayed at remote locations. Advance information about remote user actions is then visible and facilitates collaborative mediation between users. Depth information may be used to influence the process of combining the images. | 06-28-2012 |
20120166462 | AUTOMATED IMAGE DATA PROCESSING AND VISUALIZATION - The present discussion relates to automated image data processing and visualization. One example can facilitate generating a graphical user-interface (GUI) from image data that includes multiple semantically-labeled user-selectable anatomical structures. This example can receive a user selection of an individual semantically-labeled user-selectable anatomical structure. The example can locate a sub-set of the image data associated with the individual semantically-labeled user-selectable anatomical structure and can cause presentation of the sub-set of the image data on a subsequent GUI. | 06-28-2012 |