This paper presents a recognition method for human behavior identification based on motion history image theory. The motion history image has the advantage that it can record the ...
Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...
Abstract. Markov and Conditional random fields (CRFs) used in computer vision typically model only local interactions between variables, as this is computationally tractable. In t...
We propose a novel consistent max-covering scheme for
human pose estimation. Consistent max-covering formulates
pose estimation as the covering of body part polygons
on an objec...
We present an organic computing approach for very fast image processing, which we call Marching Pixels (MPs). Using an embedded massively-parallel array of processor elements (PEs...