Near-duplicate keyframe retrieval with visual keywords and semantic context

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. Categories and Subject Descriptors H.3.3 [Information Storage and Retrieval]: Information Searc...

• Type: Conference
• Year: 2007
• Where: CIVR
• Authors: Xiao Wu, Wanlei Zhao, Chong-Wah Ngo
• Keywords: CIVR 2007, Semantic Context, Video Search, Visual Keywords