A new approac to robust human motion detection

Qin Li; Jia You; Prabir Bhattacharya

A new approac to robust human motion detection

Qin Li, Jia You, Prabir Bhattacharya

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-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 language	English
Title of host publication	Proceedings of the Eighth IASTED International Conference on Intelligent Systems and Control, ISC 2005
Pages	398-403
Number of pages	6
Publication status	Published - 1 Dec 2005
Event	Eighth IASTED International Conference on Intelligent Systems and Control, ISC 2005 - Cambridge, MA, United States Duration: 31 Oct 2005 → 2 Nov 2005

Conference

Conference	Eighth IASTED International Conference on Intelligent Systems and Control, ISC 2005
Country/Territory	United States
City	Cambridge, MA
Period	31/10/05 → 2/11/05

Keywords

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

ASJC Scopus subject areas

General Engineering

Cite this

@inproceedings{1e388f175ce14606a70e902f7cbf7440,

title = "A new approac to robust human motion detection",

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.",

keywords = "Fussy Set Theory, Human Motion Detection, Image Feature Hierarchy, Image Understanding, Multiple Feature Extraction",

author = "Qin Li and Jia You and Prabir Bhattacharya",

year = "2005",

month = dec,

day = "1",

language = "English",

isbn = "0889865191",

pages = "398--403",

booktitle = "Proceedings of the Eighth IASTED International Conference on Intelligent Systems and Control, ISC 2005",

note = "Eighth IASTED International Conference on Intelligent Systems and Control, ISC 2005 ; Conference date: 31-10-2005 Through 02-11-2005",

}

TY - GEN

T1 - A new approac to robust human motion detection

AU - Li, Qin

AU - You, Jia

AU - Bhattacharya, Prabir

PY - 2005/12/1

Y1 - 2005/12/1

N2 - 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.

AB - 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.

KW - Fussy Set Theory

KW - Human Motion Detection

KW - Image Feature Hierarchy

KW - Image Understanding

KW - Multiple Feature Extraction

UR - http://www.scopus.com/inward/record.url?scp=33244455210&partnerID=8YFLogxK

M3 - Conference article published in proceeding or book

SN - 0889865191

SP - 398

EP - 403

BT - Proceedings of the Eighth IASTED International Conference on Intelligent Systems and Control, ISC 2005

T2 - Eighth IASTED International Conference on Intelligent Systems and Control, ISC 2005

Y2 - 31 October 2005 through 2 November 2005

ER -

A new approac to robust human motion detection

Abstract

Conference

Keywords

ASJC Scopus subject areas

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