Please use this identifier to cite or link to this item: https://doi.org/10.1145/1180639.1180687
Title: News video search with fuzzy event clustering using high-level features
Authors: Neo, S.-Y. 
Zheng, Y.
Chua, T.-S. 
Tian, Q.
Keywords: Event-based clustering
Video retrieval
Issue Date: 2006
Source: Neo, S.-Y.,Zheng, Y.,Chua, T.-S.,Tian, Q. (2006). News video search with fuzzy event clustering using high-level features. Proceedings of the 14th Annual ACM International Conference on Multimedia, MM 2006 : 169-172. ScholarBank@NUS Repository. https://doi.org/10.1145/1180639.1180687
Abstract: Precise automated video search is gaining in importance as the amount of multimedia information is increasing at exponential rates. One of the drawbacks that make video retrieval difficult is the lack of available semantics. In this paper, we propose to supplement the semantic knowledge for retrieval by providing useful semantic clusters derived from event entities present in the news video. These entities include the output from keywords derived from the automated speech recognition (ASR) and event-related High-level Features (HLF) extracted from the news video at the pseudo story level. Fuzzy clustering is then carried out to group similar stories together to form semantic clusters. The retrieval system utilizes these clusters to refine the re-ranking process in the Pseudo Relevance Feedback (PRF) step. Initial experiments performed on video search task using the TRECVID 2005 dataset show that the proposed approach can improve the search performance significantly.
Source Title: Proceedings of the 14th Annual ACM International Conference on Multimedia, MM 2006
URI: http://scholarbank.nus.edu.sg/handle/10635/41329
ISBN: 1595934472
DOI: 10.1145/1180639.1180687
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