Abstract: Disclosed is a facial recognition system/method, utilizing modules to perform the following routine: extracting a feature descriptor from a detected feature point of a detected face in an input image frame; and matching the extracted feature descriptor with at least one of a pre-stored facial image that is index-mapped, comprising at least a first and second round of matching, wherein the second round of matching only selects the index-mapped facial images that matched above a pre-defined threshold from the first round of matching. Optionally, the above described steps may be coupled to a Point-of-Recognition (POR) provisioning, enabling an on-demand gate-keeping and/or payment processing for an end-user at an event/venue entry or point-of-sale.

Abstract: The primary purpose of the present invention is to enable devices/machines/systems to perform an optimized video analytics on images and videos. The present invention focuses on detecting, tracking, and classifying objects in a scene. Here, the tracking is performed by comparing objects across at least two frames and then associating the objects based on a cost matrix. Some examples of the objects include, but are not limited to, persons, animals, vehicles, or any other articles or items.

Abstract: The present invention discloses methods and systems face recognition. Face recognition involves receiving an image/frame, detecting one or more faces in the image, detecting feature points for each of the detected faces in the image, aligning and normalizing the detected feature points, extracting feature descriptors based on the detected feature points and matching the extracted feature descriptors with a set of pre-stored images for face recognition.