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 ...
This paper presents an unsupervised learning algorithm that can derive the probabilistic dependence structure of parts of an object (a moving human body in our examples) automatic...
Abstract. Temporal random variation of luminance in images can manifest in film and video due to a wide variety of sources. Typical in archived films, it also affects scenes rec...
We present an original approach for motion-based retrieval involving partial query. More precisely, we propose an uni ed statistical framework both to extract entities of interest ...
This paper proposes a novel method for estimating depth from a long image sequence captured by a moving camera. Our idea for estimating a depth map is very simple; only counting i...