Learning patterns of human behavior from sensor data is extremely important for high-level activity inference. We show how to extract and label a personās activities and signiļ¬...
āThis paper presents an extended target tracking framework which uses polynomials in order to model extended objects in the scene of interest from imagery sensor data. State spac...
Christian Lundquist, Umut Orguner, Fredrik Gustafs...
In this paper, we propose a new context-sensitive Bayesian learning algorithm. By modeling the distributions of data locations by a mixture of Gaussians, the new algorithm can uti...
This paper develops a supervised dimensionality reduction method, Lorentzian Discriminant Projection (LDP), for discriminant analysis and classiļ¬cation. Our method represents the...
A frequent problem in density level-set estimation is the choice of the right features that give rise to compact and concise representations of the observed data. We present an eļ¬...