Deep Learning Based Semantic Video Indexing and Retrieval
نویسندگان
چکیده
We share the implementation details and testing results for video retrieval system based exclusively on features extracted by convolutional neural networks. We show that deep learned features might serve as universal signature for semantic content of video useful in many search and retrieval tasks. We further show that graph-based storage structure for video index allows to efficiently retrieving the content with complicated spatial and temporal search queries. Keywords—video indexing; video retrieval; shot boundary detection; graph database; semantic features; MPEG-7
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عنوان ژورنال:
- CoRR
دوره abs/1601.07754 شماره
صفحات -
تاریخ انتشار 2016