Gender recognition from body

Liangliang Cao, Mert Dikmen, Yun Fu, Thomas S. Huang

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

Abstract

This paper studies the problem of recognizing gender from full body images. This problem has not been addressed before, partly because of the variant nature of human bodies and clothing that can bring tough difficulties. However, gender recognition has high application potentials, e.g., security surveillance and customer statistics collection in restaurants, supermarkets, and even building entrances. In this paper, we build a system of recognizing gender from full body images, taken from frontal or back views. Our contributions are three-fold. First, to handle the variety of human body characteristics, we represent each image by a collection of patch features, which model different body parts and provide a set of clues for gender recognition. To combine the clues, we build an ensemble learning algorithm from those body parts to recognize gender from fixed view body images (frontal or back). Second, we relax the fixed view constraint and show the possibility to train a flexible classifier for mixed view images with the almost same accuracy as the fixed view case. At last, our approach is shown to be robust to small alignment errors, which is preferred in many applications.

Original languageEnglish (US)
Title of host publicationMM'08 - Proceedings of the 2008 ACM International Conference on Multimedia, with co-located Symposium and Workshops
Pages725-728
Number of pages4
DOIs
StatePublished - Dec 1 2008
Event16th ACM International Conference on Multimedia, MM '08 - Vancouver, BC, Canada
Duration: Oct 26 2008Oct 31 2008

Publication series

NameMM'08 - Proceedings of the 2008 ACM International Conference on Multimedia, with co-located Symposium and Workshops

Other

Other16th ACM International Conference on Multimedia, MM '08
CountryCanada
CityVancouver, BC
Period10/26/0810/31/08

Keywords

  • Gender recognition
  • Human body

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition
  • Software

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  • Cite this

    Cao, L., Dikmen, M., Fu, Y., & Huang, T. S. (2008). Gender recognition from body. In MM'08 - Proceedings of the 2008 ACM International Conference on Multimedia, with co-located Symposium and Workshops (pp. 725-728). (MM'08 - Proceedings of the 2008 ACM International Conference on Multimedia, with co-located Symposium and Workshops). https://doi.org/10.1145/1459359.1459470