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Highlights extraction from sports video based on an audio-visual marker detection framework

机译:基于视听标记检测框架从体育视频中提取亮点

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摘要

We propose to use a visual object (e.g., the baseball catcher) detection algorithm to find local, semantic objects in video frames in addition to an audio classification algorithm to find semantic audio objects in the audio track for sports highlights extraction. The highlight candidates are then further grouped into finer-resolution highlight segments, using color or motion information. During the grouping phase, many of the false alarms can be correctly identified and eliminated. Our experimental results with baseball, soccer and golf video are promising.
机译:我们建议除了使用音频分类算法在音频轨道中查找语义音频对象以进行体育赛事精彩片段提取外,还使用视觉对象(例如,棒球接球手)检测算法在视频帧中查找局部语义对象。然后,使用颜色或运动信息将高光候选者进一步分组为更高分辨率的高光片段。在分组阶段,可以正确识别并消除许多错误警报。我们在棒球,足球和高尔夫视频上的实验结果很有希望。

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