Abstract: A method and system for privacy-aware movement tracking includes receiving a series of images of a field of view, such as captured by a camera. The images containing movement of an unidentified person within the field of view. A body region corresponding to the person is detected within the images. A movement dataset for the unidentified person is generated based on tracking movement of the body region over the fired of view within the images is generated. A characterizing feature set is determined for the unidentified person. The set is associated within the movement dataset to form a first track entry. Anonymizing of the body region can be applied to remove identifying features while or prior to determining the characterizing feature set. A second track entry can be generated from a second series of images and match between the track entries can be determined. A method and system for privacy-aware operation and learning of a computer-implemented classification module is also contemplated.

Abstract: A system and method for performing distributed facial recognition divides processing steps between a user engagement device/robot, having lower processing power, and a remotely located server, having significantly more processing power. Images captured by the user engagement device/robot are processed at the device/robot by applying a first set of image processing steps that includes applying a first face detection. First processed images having at least one detected face is transmitted to the server, whereat a second set of image processing steps are applied to determine a stored user facial image matching the detected face of the first processed image. At least one user property associated to the given matching user facial image is then transmitted to the user engagement device/robot. An interactive action personalized to the user can further be performed at the user engagement device/robot.