Perception-oriented prominent region detection in video sequences using fuzzy inference neural network

Abstract

In this paper, we propose a new approach for the prominent region detection from the viewpoint of the human perception intending to construct a good pattern for content representation of the video sequences. Firstly, we partition each frame into homogeneous regions using a technique based on a non-parameter clustering algorithm. Then, in order to automatically determine the prominent importance of the different homogenous regions in a frame, we extract a number of different mise-en-scene-based perceptual features, which influence human visual attention. Finally, a modified Fuzzy Inference Neural Network is used to detect prominent regions in video sequences, due to its simple structure and superior performance for automatic fuzzy rules extraction. The extracted prominent regions could be used as a good pattern to bridge semantic gap between low-level features and semantic understanding. Experimental results show the excellent performance of the approach. © Springer-Verlag Berlin Heidelberg 2005.