Abstract: Systems, devices, method and arrangements are implemented in a variety of embodiments to facilitate motion capture of objects. Consistent with one such system, three-dimensional representations are determined for at least one object. Depth-based image data is used in the system, which includes a processing circuit configured and arranged to render a plurality of orientations for at least one object. Orientations from the plurality of orientations are assessed against the depth-based image data. An orientation is selected from the plurality of orientations as a function of the assessment of orientations from the plurality of orientations.

Abstract: Methods, systems, devices and arrangements are implemented for motion tracking. One such system for tracking at least one object articulated in three-dimensional space is implemented using data obtained from a depth sensor. The system includes at least one processing circuit configured and arranged to determine location probabilities for a plurality of object parts by identifying, from image data obtained from the depth sensor, features of the object parts. The processing circuit selects a set of poses for the at least one object based upon the determined location probabilities and generates modeled depth sensor data by applying the selected set of poses to a model of the at least one object. The processing circuit selects a pose for the at least one object model-based based upon a probabilistic comparison between the data obtained from the depth sensor and the modeled depth sensor data.

Abstract: Computer-implemented methods for providing recommendations for a given user. The computer-implemented method employs some or all of machine learning, collaborative filtering, clustering, profile data from the given user, profile data from other users, feedback data from the given user from past interactions, and feedback data from other users from past interactions to more accurately provide recommendations to the given user.