Samangooei, Sina and Nixon, Mark
Performing Content-based Retrieval of Humans using Gait Biometrics
At SAMT 2008.
In order to analyse surveillance video, we need to efficiently explore large datasets containing videos of walking humans. At survei llance-image resolution, the human walk (their gait) can be determined automatically, and more readily than other features such as the face. Effective analysis of such data relies on retrieval of video data which has been enriched using semantic annotations. A manual annotation process is time-consuming and prone to error due to subject bias. We explore the content-based retrieval of videos containing walking subjects, using semantic queries. We evaluate current biometric research using gait, unique in its effectiveness at recognising people at a distance. We introduce a set of semantic traits discernible by humans at a distance, outlining their psychological validity. Working under the premise that similarity of the chosen gait signature implies similarity of certain semantic traits we perform a set of semantic retrieval experiments using popular latent semantic analysis techniques from the information retrieval community.
Conference or Workshop Item
||Event Dates: 2/12/2008
|Venue - Dates:
||SAMT 2008, 2008-12-02
||CBIR, gait, biometrics
||Vision, Learning and Control, Southampton Wireless Group
|27 November 2008||Published|
||22 Jan 2009 11:37
||17 Apr 2017 18:54
|Further Information:||Google Scholar|
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