Reliably recovering 3D human pose from monocular video requires models that bias the estimates towards typical human poses and motions. We construct priors for people tracking usi...
Abstract. We describe progress in the automatic detection and identification of humans in video, given a minimal number of labelled faces as training data. This is an extremely cha...
The detection and pose estimation of people in images and video is made challenging by the variability of human appearance, the complexity of natural scenes, and the high dimensio...
Leonid Sigal, Michael Isard, Benjamin H. Sigelman,...
Getting trapped in suboptimal local minima is a perennial problem in model based vision, especially in applications like monocular human body tracking where complex nonlinear para...
Sequential random sampling (`Markov Chain Monte-Carlo') is a popular strategy for many vision problems involving multimodal distributions over high-dimensional parameter spac...