We introduce a new class of probabilistic latent variable model called the Implicit Mixture of Conditional Restricted Boltzmann Machines (imCRBM) for use in human pose tracking. K...
Graham Taylor, Leonid Sigal, David Fleet, Geoffrey...
Extracting meaningful 3D human motion information from video sequences is of interest for applications like intelligent humancomputer interfaces, biometrics, video browsing and ind...
In this paper we present a technique for predicting the 2D human body joints and limbs position in monocular image sequences, and reconstructing its corresponding 3D postures using...
Abstract. We propose motion manifold learning and motion primitive segmentation framework for human motion synthesis from motion-captured data. High dimensional motion capture date...
In this paper an approach to recover the 3D human body pose from static images is proposed. We adopt a discriminative learning technique to directly infer the 3D pose from appearan...
Suman Sedai, Farid Flitti, Mohammed Bennamoun, Du ...