This paper presents a learning-based method for combining the shape and appearance feature types for 3D human pose estimation from single-view images. Our method is based on clust...
We address the problem of 2D-3D pose estimation in difficult viewing conditions, such as low illumination, cluttered background, and large highlights and shadows that appear on t...
Abstract. We propose a hierarchical process for inferring the 3D pose of a person from monocular images. First we infer a learned view-based 2D body model from a single image using...
Real-time estimation of a camera’s pose relative to an object is still an open problem. The difficulty stems from the need for fast and robust detection of known objects in the s...
We propose a generative statistical approach to human motion modeling and tracking that utilizes probabilistic latent semantic (PLSA) models to describe the mapping of image featu...