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首页> 外文会议>International Conference on Information Technology - New Generations >Short Boundary Detection Using Spatial-Temporal Features
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Short Boundary Detection Using Spatial-Temporal Features

机译：使用空间时间特征的短边界检测

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摘要

Shot boundary detection is a major and challenging job in any video processing solutions. Different features are used for detecting shot boundaries in a video. Choice of features depends on the nature of processing. Mostly features are extracted from either spatial domain (visual features) or from temporal domain (motion information). To obtain more accuracy normally high level features are used but these features need complex computations. On the other hand low-level features like colour and brightness are easy to extract and compute but these features have less tolerance towards small changes in the frame. Similarly features in temporal domain have their limitations - they mostly ignore the spatial domain and hence give false results. In this proposed solution, features from both spatial and temporal domains are combined. In spatial domain brightness information is used that is easy to extract and fast to compute. From spatial domain motion information is used. Motion information is extracted from sub-blocks that add spatial information as well. Finally both the results are combined resulting in higher accuracy, more sensitivity and tolerance.
机译：拍摄边界检测是任何视频处理解决方案中的主要和具有挑战性的工作。不同的功能用于检测视频中的镜头边界。特征的选择取决于处理的性质。主要是从空间域（视觉特征）或来自时间域（运动信息）中提取的特征。为了获得更多的精度，通常使用高级别功能，但这些功能需要复杂的计算。另一方面，像颜色和亮度等的低级功能很容易提取和计算，但这些功能对框架的小变化具有更少的耐受性。类似地，时间域中的特征具有它们的局限性 - 它们主要忽略空间域，因此给出错误的结果。在该提出的解决方案中，组合来自空间和时间域的特征。在空间域中的亮度信息中，使用易于提取并快速计算。使用空间域运动信息。从添加空间信息的子块中提取运动信息。最后，结果都是相结合的，导致更高的准确性，更灵敏度和耐受性。

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