Fabrice Moscheni

Learn More
This paper proposes a technique for spatiotemporal segmentation to identify the objects present in the scene represented in a video sequence. This technique processes two consecutive frames at a time. A region-merging approach is used to identify the objects in the scene. Starting from an oversegmentation of the current frame, the objects are formed by(More)
Motion estimation and compensation techniques are widely used in video coding. This paper addresses the problem of the trade-oo between the motion and the prediction error information. Under some realistic hypotheses, the transmission cost of these two components can be estimated. Therefore, we obtain a criterion which controls the motion estimation process(More)
In the framework of sequence coding, motion estimation and compensation has been shown to be very ef-cient at removing temporal redundancy. The motion existing in a scene can be mainly seen as arising from local motions superimposed to the camera motion. In this paper, a new two stage global/local motion estimation approach is presented. The global motion(More)
We present an improved object tracking algorithm in the context of spatio-temporal segmentation. By incorporating invariants for the spatial characterization, the information supplied by the tracking algorithm to the current segmentation is extended from a purely temporal to a more comprehensive spatio{temporal description of the objects in the scene.(More)
The problem to segment an image sequence in terms of regions characterized by a coherent motion is among the most challenging in image sequence analysis. This paper proposes a new technique which sequentially re-nes the segmentation and the motion estimation by combining static segmentation and motion information. Simulation results show the eeciency of the(More)