Eztracting the Highlight Events of Baseball Videos Using a Model-indezing Decision Approach

摘要：

This study presents a real-time highlight extraction system, based on a model-indexing decision approach, to detect and classify highlight events in baseball games. The system has several stages: caption extraction, caption identification, content recognition and model-indexing decision. A superimposed caption in the baseball videos is extracted using a multi-frame averaging technique. The caption is classified once it is extracted. The corresponding caption model, including the size and position of the individual caption data, is adopted to segment the caption content accurately into individual data. Based on the change status of the caption content, a novel model-indexing decision approach is proposed to detect and classify the highlight events of the baseball videos. Experimental results demonstrate that the proposed approach is very efficient for classifying highlight events. Furthermore, the performance of the proposed approach can be improved by 9.5% over the rule-based approach.

作者: Yih-Ming Su Chi-Fa Chen Chia-Yen Chen

作者单位: Department of Electronic Engineering, I-Shou University, Kaohsiung County, Taiwan Department of Electrical Engineering, I-Shou University, Kaohsiung County, Taiwan Department of Computer Science and Information Engineering, National Kaohsiung University, Kaohsiung

会议类型: 国际会议

会议名称: 2008 International Conference on Audio，Language and Image Processing(2008国际声音、语言、图像过程大会)

会议地点: 镇江

会议语种:英文

页码: 509-513

在线出版日期: 2008-07-07（万方平台首次上网日期，不代表论文的发表时间）