Scene Salience Computation for Media
Wei We · Journal of Chinese Computer Systems · 2014
Referring to integrating attention muti-control strategies in human visual system,computational model for video salience analysis are built in this paper. The model is composed of control space model and grid model facing implement. In control space, multi-control strategies for video content understanding are unified. And,control strategy is mapped into implementation by grid. Then,a multi-path conspicuity computing method( MCCM) conforming to computation model for video scene analysis is presented. First,multi resolution pyramids and centre-surround difference through across-scale difference are used in order to compute intensity feature maps,color feature maps,and orientation feature maps for conspicuity. Then,dynamic information areas are extracted w ith background registration technique. After that,dynamic feature conspicuity map is obtained follow ing intensity centre-surround difference and normalization operator. Finally,four feature conspicuity maps are fused using Pulse Coupled Neural netw ork( PCNN) w ith adaptive linking strength parameter. Experiment results contrast to other method show that the method in this paper can compute w hole conspicuity maps w ith dynamic and still saliency information,w hich is suited for media scene analysis.