Markov random fields for sketch based video retrieval


We describe a new system for searching video databases using free-hand sketched queries. Our query sketches depict both object appearance and motion, and are annotated with keywords that indicate the semantic category of each object. We parse space-time volumes from video to form graph representation, which we match to sketches under a Markov Random Field (MRF) optimization. The MRF energy function is used to rank videos for relevance and contains unary, pairwise and higher-order potentials that reflect the colour, shape, motion and type of sketched objects. We evaluate performance over a dataset of 500 sports footage clips.

DOI: 10.1145/2461466.2461510

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@inproceedings{Hu2013MarkovRF, title={Markov random fields for sketch based video retrieval}, author={Rui Hu and Stuart James and Tinghuai Wang and John P. Collomosse}, booktitle={ICMR}, year={2013} }