Upper Body Detection in Unconstrained Still Images

Research output: Chapter in Book/Conference paperConference paper

Abstract

The detection of upper bodies is fundamental to many computer vision tasks, with human pose estimation being our focus. Accurate upper body detection improves the robustness and reduces the search space for top-down as well as bottom-up approaches for pose estimation. This paper focuses on a particularly challenging task of detecting upper bodies from unconstrained still images. We propose a method that fuses the reliability of face detectors with the robustness of people detection based on HoG descriptors to improve the accuracy of upper body detection from monocular still images with cluttered background, poor illumination, motion blur and high-degree of occlusion. We compare the performance of the proposed method with six existing face and upper body detectors. Despite the relatively simple concept behind the proposed detector, it performed on par with the state of the art systems using challenging test images from the Buffy Stickmen v2.1 dataset.
Original languageEnglish
Title of host publication2011 6TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA)
Place of PublicationUSA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages287-292
VolumeSingle
ISBN (Print)9781424487554
Publication statusPublished - 2011
Event6th IEEE Conference on Industrial Electronics and Applications (ICIEA2011) - Beijing, China
Duration: 21 Jun 201123 Jun 2011

Conference

Conference6th IEEE Conference on Industrial Electronics and Applications (ICIEA2011)
Abbreviated titleICIEA2011
CountryChina
CityBeijing
Period21/06/1123/06/11

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Wong, W., Huynh, D., & Bennamoun, M. (2011). Upper Body Detection in Unconstrained Still Images. In 2011 6TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA) (Vol. Single, pp. 287-292). USA: IEEE, Institute of Electrical and Electronics Engineers.