A Novel Scheme for Video Similarity Detection
In this paper, a new two-phase scheme for video similarity detection is proposed. For each video sequence, we extract two kinds of signatures with different granularities: coarse and fine. Coarse signature is based on the Pyramid Density Histogram (PDH) technique and fine signature is based on the N...
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| Main Authors: | , , |
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| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2003
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/2401 https://ink.library.smu.edu.sg/context/sis_research/article/3401/viewcontent/civr03_published.pdf |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | In this paper, a new two-phase scheme for video similarity detection is proposed. For each video sequence, we extract two kinds of signatures with different granularities: coarse and fine. Coarse signature is based on the Pyramid Density Histogram (PDH) technique and fine signature is based on the Nearest Feature Trajectory (NFT) technique. In the first phase, most of unrelated video data are filtered out with respect to the similarity measure of the coarse signature. In the second phase, the query video example is compared with the results of the first phase according to the similarity measure of the fine signature. Different from the conventional nearest neighbor comparison, our NFT based similarity measurement method well incorporates the temporal order of video sequences. Experimental results show that our scheme achieves better quality results than the conventional approach. |
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