Visual Resampling for Pseudo-Relevance Feedback during Speech-based Video Retrieval
نویسندگان
چکیده
A method is proposed that makes use of visual reranking to selectively sample feedback sets for Pseudo-Relevance-Feedback during speechtranscript-based video retrieval. Observed performance improvement is indicative of the ability of visual reranking to increase the relevance density of the feedback set.
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تاریخ انتشار 2009