Multiple Curvature Based Approach To Human Upper Body Parts Detection With Connected Ellipse Model Fine-Tuning

Yi Da Xu, Michael Kemp

Research output: Book chapter/Published conference paperConference paperpeer-review

8 Citations (Scopus)
18 Downloads (Pure)

Abstract

In this paper, we discuss an effective method for detecting human upper body parts from a 2D image silhouette using curvature analysis and ellipse fitting. First we smooth the silhouette so that we can determine just the global features: the head, hands and armpits. Next we reduce the smoothing to detect the local features of the neck and elbows. We model the human upper body by multiple connected ellipses. Thus we segment the body by the extracted features. Ellipses are fitted to each segment. Lastly, we apply a non-linear least square method to minimize the differences between the connected ellipse model and the edge of the silhouette.
Original languageEnglish
Title of host publicationIEEE International Conference on Image Processing
Place of PublicationUSA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages2577-2580
Number of pages4
ISBN (Electronic)9781424456536
DOIs
Publication statusPublished - 2009
EventICIP 16th International Conference - Cairo, Egypt, Egypt
Duration: 07 Nov 200910 Nov 2009

Conference

ConferenceICIP 16th International Conference
Country/TerritoryEgypt
Period07/11/0910/11/09

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