| Title | Correlation-Based Retrieval for Heavily Changed Near-Duplicate Videos |
| Authors | Liu, Jiajun Huang, Zi Shen, Heng Tao Cui, Bin |
| Affiliation | Univ Queensland, Sch Informat Technol & Elect Engn, Brisbane, Qld 4072, Australia. Peking Univ, Dept Comp Sci, Beijing, Peoples R China. |
| Keywords | Design Algorithms Experimentation Near-duplicate video correlation-based retrieval similarity-based retrieval SCALE |
| Issue Date | 2011 |
| Publisher | acm transactions on information systems |
| Citation | ACM TRANSACTIONS ON INFORMATION SYSTEMS.2011,29,(4). |
| Abstract | The unprecedented and ever-growing number of Web videos nowadays leads to the massive existence of near-duplicate videos. Very often, some near-duplicate videos exhibit great content changes, while the user perceives little information change, for example, color features change significantly when transforming a color video with a blue filter. These feature changes contribute to low-level video similarity computations, making conventional similarity-based near-duplicate video retrieval techniques incapable of accurately capturing the implicit relationship between two near-duplicate videos with fairly large content modifications. In this paper, we introduce a new dimension for near-duplicate video retrieval. Different from existing near-duplicate video retrieval approaches which are based on video-content similarity, we explore the correlation between two videos. The intuition is that near-duplicate videos should preserve strong information correlation in spite of intensive content changes. More effective retrieval with stronger tolerance is achieved by replacing video-content similarity measures with information correlation analysis. Theoretical justification and experimental results prove the effectiveness of correlation-based near-duplicate retrieval. |
| URI | http://hdl.handle.net/20.500.11897/394135 |
| ISSN | 1046-8188 |
| DOI | 10.1145/2037661.2037666 |
| Indexed | SCI(E) EI |
| Appears in Collections: | 信息科学技术学院 |
