Rapid Localisation and Retrieval of Human Actions with Relevance Feedback

Simon Jones, Ling Shao

Research output: Contribution to conferencePaper

4 Citations (Scopus)

Abstract

As increasing levels of multimedia data online require more sophisticated methods to organise this data, we present a practical system for performing rapid localisation and retrieval of human actions from large video databases. We first temporally segment the database and calculate a histogram-match score for each segment against the query. High-scoring, adjacent segments are joined into candidate localised regions using a noise-robust localisation algorithm, and each candidate region is then ranked against the query. Experiments show that this method surpasses the efficiency of previous attempts to perform similar action searches with localisation. We demonstrate how results can be enhanced using relevance feedback, considering how relevance feedback can be effectively applied in the context of localisation.
Original languageEnglish
DOIs
Publication statusPublished - Aug 2013
EventCAIP 2013 - 15th International Conference on Computer Analysis of Images and Patterns - York, UK
Duration: 1 Aug 2013 → …

Conference

ConferenceCAIP 2013 - 15th International Conference on Computer Analysis of Images and Patterns
Period1/08/13 → …

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