Robust human motion detection via fuzzy set based image understanding

Qin Li, Jia You

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


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 single 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 fuzzy compactness based detection of interesting points and fuzzy blobs, 2) adaptive image segmentation via multiple features, 3) Hierarchical motion detection, 4) a flexible model of human motion adapted in both rigid and non-rigid conditions, and 5) Fuzzy decision making via multiple features.
Original languageEnglish
Title of host publicationImage Processing
Subtitle of host publicationAlgorithms and Systems, Neural Networks, and Machine Learning - Proceedings of SPIE-IS and T Electronic Imaging
Publication statusPublished - 17 Apr 2006
EventImage Processing: Algorithms and Systems, Neural Networks, and Machine Learning - San Jose, CA, United States
Duration: 16 Jan 200618 Jan 2006


ConferenceImage Processing: Algorithms and Systems, Neural Networks, and Machine Learning
Country/TerritoryUnited States
CitySan Jose, CA


  • Fussy Set Theory
  • Fuzzy Compactness
  • Hierarchical Detection
  • Human Motion Detection
  • Image Understanding

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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