In this paper, we present a patch-based regression framework for addressing the human age and head pose estimation problems. Firstly, each image is encoded as an ensemble of order...
Shuicheng Yan, Xi Zhou, Ming Liu, Mark Hasegawa-Jo...
A probabilistic method for tracking 3D articulated human figures in monocular image sequences is presented. Within a Bayesian framework, we define a generative model of image appea...
Hedvig Sidenbladh, Michael J. Black, David J. Flee...
Abstract. We propose motion manifold learning and motion primitive segmentation framework for human motion synthesis from motion-captured data. High dimensional motion capture date...
This paper presents a method for markerless human motion capture using a single camera. It uses tree-based filtering to efficiently propagate a probability distribution over pos...
Abstract. We present two data-driven importance distributions for particle filterbased articulated tracking; one based on background subtraction, another on depth information. In ...