Please use this identifier to cite or link to this item: https://hdl.handle.net/1783.1/55196
ASVTDECTOR: A Practical Near Duplicate Video Retrieval System
| Author |
Zhou, Xiangmin
Chen, Lei 
|
|---|---|
| Issue Date | 2013 |
| Source | Proceedings - International Conference on Data Engineering, 2013, article number 6544941, p. 1348-1351 |
| Abstract | In this paper, we present a system, named ASVTDECTOR, to retrieve the near duplicate videos with large variations based on an 3D structure tensor model, named ASVT series, over the local descriptors of video segments. Different from the traditional global feature-based video detection systems that incur severe information loss, ASVT model is built over the local descriptor set of each video segment, keeping the robustness of local descriptors. Meanwhile, unlike the traditional local feature-based methods that suffer from the high cost of pair-wise descriptor comparison, ASVT model describes a video segment as an 3D structure tensor that is actually a 3 x 3 matrix, obtaining high retrieval efficiency. In this demonstration, we show that, given a clip, our ASVTDETECTOR system can effectively find the near-duplicates with large variations from a large collection in real time. |
| Conference | 29th International Conference on Data Engineering, ICDE 2013, Brisbane, QLD, Australia, 8-11 April, 2013 |
| DOI | 10.1109/ICDE.2013.6544941 |
| ISSN | 1084-4627 |
| ISBN | 9781467349086 |
| Language | English |
| Type | Conference paper |
| Access |
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