We present a new algorithm to detect humans in still images utilizing covariance matrices as object descriptors. Since these descriptors do not lie on a vector space, well known m...
We propose a data-driven, hierarchical approach for the analysis of human actions in visual scenes. In particular, we focus on the task of in-house assisted living. In such scenar...
This paper presents an approach for human activity recognition by representing the frames of the video sequence with the distribution of local motion features and their spatiotemp...
In this paper, we investigate the utility of static anthropometric distances as a biometric for human identification. The 3D landmark data from the CAESAR database is used to form...
For the management of a large number of motion data for humanoid virtual actors we propose to use a database system to store and retrieve motion data with additional information. ...