False Positive Eliminating Using Frame Association Information

As a fundamental technology of human motion analysis, video based pose estimation has attracted more and more attention of researchers. While most mainstream methods treated videos as a collection of unrelated frames, random false positives caused by light and shadow changes will bring greater uncertainty to the results of human body estimation. To eliminate these false positives in multi-person 2D pose estimation, a method of multi-person 2D pose estimation using the time-space relationship of adjacent frames is proposed. At first, Frame Association Information(FAI) is defined to represent the relationship between person objects in adjacent frames, which contents similarity of position, size and poses. Then, a method of false positives eliminating is designed using FAIs between frames, which can identify and remove false positives in frames according to their similarities to human objects in a benchmark frame. The following experiments show the effectiveness of our method.