A Novel Attention-Based Key-Frame Determination Method

This paper presents a novel key-frame detection method that combines the visual saliency-based attention features with the contextual game status information for sports videos. Two critical issues of the attention-based video content analysis are addressed: 1) the visual attention characteristics when a user is watching a video clip and 2) extracting the degree of excitement about the on-going game status. First, the object-oriented visual attention map and the algorithm of determining the contextual attention are presented. The procedure of the contextual inference is used to simulate how the game status attracts the viewers. Second, a fusion methodology of visual and contextual attention analysis based on the characteristics of human excitement is introduced. In addition, the amount of key-frames is determined by using the contextual attention score, while the key-frame determination depends on integrating all the visual attention scores. In experimental results, it demonstrates the robustness of the proposed system for basketball and baseball programs.