Abstract
Bag-of-visual-words (BoW) has been popular for visual classification in recent years. In this paper, we propose a novel BoW expansion method to alleviate the effect of visual word correlation problem. We achieve this by diffusing the weights of visual words in BoW based on visual word relatedness, which is rigorously defined within a visual ontology. The proposed method is tested in video indexing experiment on TRECVID-2006 video retrieval benchmark, and an improvement of 7% over the traditional BoW is reported.
| Original language | English |
|---|---|
| Title of host publication | ACM SIGIR 2008 - 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Proceedings |
| Pages | 769-770 |
| DOIs | |
| Publication status | Published - 2008 |
| Event | 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, ACM SIGIR 2008 - Singapore, Singapore Duration: 20 Jul 2008 → 24 Jul 2008 |
Conference
| Conference | 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, ACM SIGIR 2008 |
|---|---|
| Place | Singapore |
| City | Singapore |
| Period | 20/07/08 → 24/07/08 |
Research Keywords
- Bag-of-visual-words
- Expansion
- Video indexing
- Visual relatedness
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