A new approac to robust human motion detection

Qin Li, Jia You, Prabir Bhattacharya

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

This paper presents an image understanding approach to monitor human movement and identify the abnormal circumstance by robust motion detection for the care of the elderly in a home-based environment. In contrast to the conventional approaches which apply either a fixed feature extraction scheme or a fixed object model for motion detection and tracking, we introduce a multiple feature extraction scheme for robust motion detection. The proposed algorithms include 1) multiple image feature extraction including the detection of interesting points and color clusters, 2)adaptive thresholding selection based on the compactness measures of fuzzy sets in image feature space, 3) a flexible model of human motion adapted in both rigid and non-rigid conditions, and 4) an optimized algorithm for object tracking and fuzzy decision making.
Original languageEnglish
Title of host publicationProceedings of the Eighth IASTED International Conference on Intelligent Systems and Control, ISC 2005
Pages398-403
Number of pages6
Publication statusPublished - 1 Dec 2005
EventEighth IASTED International Conference on Intelligent Systems and Control, ISC 2005 - Cambridge, MA, United States
Duration: 31 Oct 20052 Nov 2005

Conference

ConferenceEighth IASTED International Conference on Intelligent Systems and Control, ISC 2005
CountryUnited States
CityCambridge, MA
Period31/10/052/11/05

Keywords

  • Fussy Set Theory
  • Human Motion Detection
  • Image Feature Hierarchy
  • Image Understanding
  • Multiple Feature Extraction

ASJC Scopus subject areas

  • Engineering(all)

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