POSE ESTIMATION BASED ON CRITICAL POINT ANALYSIS

摘要

Methods and systems for estimating a pose of a subject. The subject can be a human, an animal, a robot, or the like. A camera receives depth information associated with a subject (310), a pose estimation module to determine a pose or action of the subject from images, and an interaction module to output a response to the perceived pose or action. The pose estimation module separates portions of the image containing the subject into classified and unclassified portions The portions can be segmented using k-means clustering The classified portions can be known objects, such as a head and a torso, that are tracked across the images The unclassified portions are swept across an x and y axis to identify local minimums and local maximums The critical points are derived from the local minimums and local maximums (320) Potential joint sections are identified by connecting various cπtical points and the joint sections having sufficient probability of corresponding to an object on the subject are selected to generate a skeletal structure based on which a pose of the subject is determined (330).