In this paper, we aim to develop a framework for continuous query processing in spatio-temporal databases. The proposed framework distinguishes itself from other query processors b...
While crowds of various subjects may offer applicationspecific cues to detect individuals, we demonstrate that for the general case, motion itself contains more information than p...
We describe a probabilistic framework for recognizing human activities in monocular video based on simple silhouette observations in this paper. The methodology combines kernel pr...
Motion Compensated Temporal Filtering (MCTF) has proved to be an efficient coding tool in the design of open-loop scalable video codecs. In this paper we propose a MCTF video codi...
This paper presents a novel framework for applying semantic labels to events within a track. A track is a two-dimensional (2D) or a three-dimensional (3D) signal in time where eac...