Near-duplicate keyframe retrieval with visual keywords and semantic context

• Main Authors: WU, Xiao, ZHAO, Wan-Lei, NGO, Chong-wah
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2007
• Subjects: Image retrieval; Language model; Multiple modalities; Near-duplicate keyframe; News videos; Similarity measure; Databases and Information Systems; Theory and Algorithms
• Online Access: https://ink.library.smu.edu.sg/sis_research/6445; https://ink.library.smu.edu.sg/context/sis_research/article/7448/viewcontent/1282280.1282309.pdf
• Institution: Singapore Management University

Near-duplicate keyframes (NDK) play a unique role in large-scale video search, news topic detection and tracking. In this paper, we propose a novel NDK retrieval approach by exploring both visual and textual cues from the visual vocabulary and semantic context respectively. The vocabulary, which provides entries for visual keywords, is formed by the clustering of local keypoints. The semantic context is inferred from the speech transcript surrounding a keyframe. We experiment the usefulness of visual keywords and semantic context, separately and jointly, using cosine similarity and language models. By linearly fusing both modalities, performance improvement is reported compared with the techniques with keypoint matching. While matching suffers from expensive computation due to the need of online nearest neighbor search, our approach is effective and efficient enough for online video search.