A challenging gait database for office surveillance

Tee Connie, Michael Goh, Thian Song Ong, Hossein Lessan Toussi, Andrew Beng Jin Teoh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Gait recognition has become increasingly important in the area of automated human identification. Several databases have been established to enable researchers to evaluate the different covariates affecting the performance of gait recognition. Recently, most of the factors like clothing variation, speed changes, and multiple view angles have been sufficiently addressed. We think it is time to introduce a more challenging database to encourage researchers to look into the harder aspects of gait recognition. The proposed database simulates an office environment as surveillance cameras are often used in offices. The database include difficult conditions like walking with umbrella which portraits a 'three-legged' walking pattern, load carriage that occludes the body part, and footwear like high-heeled shoes which alter the way that people walk. We believe the proposed database containing reasonable amount of testing samples will be able to provide an avenue for the research community to advance in the gait recognition field.

Original languageEnglish
Title of host publicationProceedings of the 2013 6th International Congress on Image and Signal Processing, CISP 2013
Pages1670-1675
Number of pages6
DOIs
Publication statusPublished - 2013
Event2013 6th International Congress on Image and Signal Processing, CISP 2013 - Hangzhou, China
Duration: 2013 Dec 162013 Dec 18

Publication series

NameProceedings of the 2013 6th International Congress on Image and Signal Processing, CISP 2013
Volume3

Other

Other2013 6th International Congress on Image and Signal Processing, CISP 2013
CountryChina
CityHangzhou
Period13/12/1613/12/18

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Signal Processing

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