The majority of existing tracking algorithms are based on the maximum a posteriori (MAP) solution of a probabilistic framework using a Hidden Markov Model, where the distribution ...
This paper addresses the problem of simultaneous tracking of multiple targets in a video. We first apply object detectors to every video frame. Pairs of detection responses from ...
We treat tracking as a matching problem of detected keypoints between successive frames. The novelty of this paper is to learn classifier-based keypoint descriptions allowing to i...
To implement a persistent tracker, we build a set of viewdependent object appearance models adaptively and automatically while tracking an object under different viewing angles. T...
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...