Human Pose Co-Estimation and Applications
Human Pose Co-Estimation and Applications is a scholarly work, published in 2012 in ''IEEE Transactions on Pattern Analysis and Machine Intelligence'' and ''IEEE Transactions on Software Engineering''. The main subjects of the publication include prior probability, task, Multiple object tracking, pattern recognition, stereopsis, pose, artificial intelligence, computer science, machine learning, Articulated body pose estimation, 3D pose estimation, image subtraction, and computer vision. The authors show that PCE improves pose estimation accuracy over estimating each person independently.