Motion Activity Based Shot Identification and Closed Caption Localization for Video Structuring

• Main Authors: Shu-Jiuan Lin, 林淑娟
• Other Authors: Suh-Yin Lee
• Format: Others
• Language: en_US
• Published: 2002
• Online Access: http://ndltd.ncl.edu.tw/handle/90085530504310189590

碩士 === 國立交通大學 === 資訊工程系 === 90 === In this paper, we propose a novel approach to generate the table of video content based on shot description of motion activity and textual information of closed caption in MPEG-Ⅱ sports videos. In order to speed up in scene change detection, instead of examining scene cut frame by frame, GOP-based approach first checks video streams GOP by GOP and then finds out the actual scene boundaries in the frame level. Segmented shots are described by the proposed object-based motion activity descriptor. The descriptor is computed based on the object 2D-histogram, in which long-term consistency of spatial-temporal relationship of moving objects within video shots is considered. Utilizing the characterized features of motion activity in video shots, video clips are recognized by the proposed algorithm of shot identification. Subsequently, the specific shots of interest are selected and the proposed mechanism of closed caption localization is exploited to detect captions in these shots. Moreover, the SOM (Self-Organization Map) based algorithm is designed as a filter to distinguish the superimposed closed captions from the high-textured background regions. Finally, we can construct a sports video content visualization system and provide the table of video content composed of the hierarchical structure of story units, consecutive shots and closed captions. Furthermore, we supply users with the dynamic tree structure of video content. The experimental results show the effectiveness of the proposed system and reveal the feasibility of the hierarchical structuring of video content.