Keyframe retrieval by keypoints: Can point-to-point matching help?

• Main Authors: ZHAO, Wanlei, JIANG, Yu-Gang, NGO, Chong-Wah
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2006
• Subjects: Color Histogram; Background Clutter; Locality Sensitive Hash; Maximal Stable Extreme Region; Video Search; Databases and Information Systems; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/6604; https://ink.library.smu.edu.sg/context/sis_research/article/7607/viewcontent/Keyframe_retrieval_by_keypoints.pdf
• Institution: Singapore Management University

Bag-of-words representation with visual keypoints has recently emerged as an attractive approach for video search. In this paper, we study the degree of improvement when point-to-point (P2P) constraint is imposed on the bag-of-words. We conduct investigation on two tasks: near-duplicate keyframe (NDK) retrieval, and high-level concept classification, covering parts of TRECVID 2003 and 2005 datasets. In P2P matching, we propose a one-to-one symmetric keypoint matching strategy to diminish the noise effect during keyframe comparison. In addition, a new multi-dimensional index structure is proposed to speed up the matching process with keypoint filtering. Through experiments, we demonstrate that P2P constraint can significantly boost the performance of NDK retrieval, while showing competitive accuracy in concept classification of broadcast domain.