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In this paper, we describe an approach to combining text and visual features from MPEG-7 descriptions of video. A video retrieval process is aligned to a text retrieval process based on the TF*IDF vector space model via clustering of low-level visual features. Our assumption is that shots within the same cluster are not only similar visually but also semantically, to a certain extent. Our experiments on the TRECVID2002 and TRECVID2003 collections show that adding extra meaning to a shot based on the shots from the same cluster is useful when each video in a collection contains a high proportion of similar shots, for example in documentaries.
@inproceedings{1009097, author = {Jiamin Ye and Alan F. Smeaton}, title = {Aggregated feature retrieval for MPEG-7 via clustering}, booktitle = {SIGIR '04: Proceedings of the 27th annual international conference on Research and development in information retrieval}, year = {2004}, isbn = {1-58113-881-4}, pages = {514--515}, location = {Sheffield, United Kingdom}, doi = {http://doi.acm.org/10.1145/1008992.1009097}, publisher = {ACM Press}, }  ©2005 Association for Computing Machinery |
