Abstract: A cropped bounding box selection operation is performed on a video captured by a video capture and playback system, to select one or more cropped bounding boxes from the video for processing by a face detection operation. The cropped bounding box selection operation identifies objects from the video images and assigns a ranking to each identified object based on certain priority criteria; one or more cropped bounding boxes corresponding to the objects with the highest ranking(s) are then processed by the face detection operation to detect a face in each object.

Abstract: A cropped bounding box selection operation is performed on a video captured by a video capture and playback system, to select one or more cropped bounding boxes from the video for processing by a face detection operation. The cropped bounding box selection operation identifies objects from the video images and assigns a ranking to each identified object based on certain priority criteria; one or more cropped bounding boxes corresponding to the objects with the highest ranking(s) are then processed by the face detection operation to detect a face in each object.

Abstract: This invention describes methods and systems for the automated facial landmark localization. Our approach proceeds from sparse to dense landmarking steps using a set of models to best account for the shape and texture variation manifested by facial landmarks across pose and expression. We also describe the use of an l1-regularized least squares approach that we incorporate into our shape model, which is an improvement over the shape model used by several prior Active Shape Model (ASM) based facial landmark localization algorithms.