Refinement of extracted visual attention areas in video sequences

Visual attention extraction is the ability to rapidly detect the interesting section of a given scene, which is called attention area or region of interest (ROI) in some literature. However, because of the inherent disadvantages of the current attention model structure, the resulted visual attention area is instable along time - that is, the extracted attention areas are quite different even between neighboring frames which are similar in content. Such an un-smooth trajectory of attention areas will lead to impressive subjective quality degradation in attention area based applications like content based video streaming/compression, and this problem cannot be solved simply by smoothing filters. In this paper, we present a strategy to generate stable attention area across time through methods of temporal emendation.