2015/04/30 by Bugra Tekin, Tekin, Bugra, Xiaolu Sun +7 · 1 citation
Computer Science · Engineering · #Human Pose and Action Recognition #Human Motion and Animation #Video Surveillance and Tracking Methods
paper · pdf · doi:10.48550/arxiv.1504.08200
We propose an efficient approach to exploiting motion information from consecutive frames of a video sequence to recover the 3D pose of people. Instead of computing candidate poses in individual frames and then linking them, as is often done, we regress directly from a spatio-temporal block of frames to a 3D pose in the central one. We will demonstrate that this approach allows us to effectively overcome ambiguities and to improve upon the state-of-the-art on challenging sequences.