In this paper we present a probabilistic framework for tracking objects based on local dynamic segmentation. We view the segn to be a Markov labeling process and abstract it as a ...
Model-based 3D tracker estimate the position, rotation, and joint angles of a given model from video data of one or multiple cameras. They often rely on image features that are tr...
We present a new framework for robust 3D tracking, using a dynamic data driven coupling of continuous and discrete methods to overcome their limitations. Our method uses primarily ...
Abstract. This paper presents a novel pixelwise representation for visual tracking that models both the spatial structure and dynamics of a target in a unified fashion. The represe...
In this paper, we present a novel approach for tracking a lecturer during the course of his speech. We use features from multiple cameras and microphones, and process them in a jo...
Kai Nickel, Tobias Gehrig, Rainer Stiefelhagen, Jo...