PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Motion-sketch based Video Retrieval using a Trellis Levenshtein Distance
Rui Hu, Mark Barnard and John Collomosse
In: ICPR 2010, Istanbul, Turkey(2010).

Abstract

We present a fast technique for retrieving video clips using free-hand sketched queries. Visual keypoints within each video are detected and tracked to form short trajectories, which are clustered to form a set of space-time tokens summarising video content. A Viterbi process matches a space-time graph of tokens to a description of colour and motion extracted from the query sketch. Inaccuracies in the sketched query are ameliorated by computing path cost using a Levenshtein (edit) distance. We evaluate over datasets of sports footage.

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EPrint Type:Conference or Workshop Item (Oral)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
Information Retrieval & Textual Information Access
ID Code:8341
Deposited By:John Collomosse
Deposited On:30 October 2011

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