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Visual descriptors based video quality assessment using outlier model
Visual descriptors based video quality assessment using outlier model
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机译:使用离群模型的基于视觉描述符的视频质量评估
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摘要
System and method for identifying erroneous videos and assessing video quality is provided. Feature vectors are generated corresponding to a plurality of frames associated with the one or more videos. The feature vectors are subsequently subjected to anomaly detection to obtain first and second normalized path lengths and normalized anomaly measures. The first and second normalized path lengths and normalized anomaly measures are provided to a regression model to identify the erroneous video.
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