東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Videosurveillance intelligente pour ...

Rougier, Caroline.

Linked to FindBook

Google Book

Amazon

博客來

Videosurveillance intelligente pour la detection de chutes chez les personnes agees.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Videosurveillance intelligente pour la detection de chutes chez les personnes agees./
Author:	Rougier, Caroline.
Description:	149 p.
Notes:	Source: Dissertation Abstracts International, Volume: 72-01, Section: B, page: 0502.
Contained By:	Dissertation Abstracts International72-01B.
Subject:	Gerontology. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=NR67195
ISBN:	9780494671955

Videosurveillance intelligente pour la detection de chutes chez les personnes agees.
Rougier, Caroline.

Videosurveillance intelligente pour la detection de chutes chez les personnes agees. - 149 p.

Source: Dissertation Abstracts International, Volume: 72-01, Section: B, page: 0502.

Thesis (Ph.D.)--Universite de Montreal (Canada), 2010.

Developed countries like Canada have to adapt to a growing population of seniors. A majority of seniors reside in private homes and most of them live alone, which can be dangerous in case of a fall, particularly if the person cannot call for help. Video surveillance is a new and promising solution for healthcare systems to ensure the safety of elderly people at home.

ISBN: 9780494671955Subjects--Topical Terms:

533633
Gerontology.

Videosurveillance intelligente pour la detection de chutes chez les personnes agees.
LDR:03084nam 2200349 4500 001 1403694
005 20111111143222.5
008 130515s2010 ||||||||||||||||| ||fre d
020 $a 9780494671955
035 $a (UMI)AAINR67195
035 $a AAINR67195
040 $a UMI $c UMI
100 1 $a Rougier, Caroline. $3 1682971
245 1 0 $a Videosurveillance intelligente pour la detection de chutes chez les personnes agees.
300 $a 149 p.
500 $a Source: Dissertation Abstracts International, Volume: 72-01, Section: B, page: 0502.
502 $a Thesis (Ph.D.)--Universite de Montreal (Canada), 2010.
520 $a Developed countries like Canada have to adapt to a growing population of seniors. A majority of seniors reside in private homes and most of them live alone, which can be dangerous in case of a fall, particularly if the person cannot call for help. Video surveillance is a new and promising solution for healthcare systems to ensure the safety of elderly people at home.
520 $a Concretely, a camera network would be placed in the apartment of the person in order to automatically detect a fall. When a fall is detected, a message would be sent to the emergency center or to the family through a secure Internet connection. For a low cost system, we must limit the number of cameras to only one per room, which leads us to explore monocular methods for fall detection.
520 $a We first studied 2D information (images) by analyzing the shape deformation during a fall. Normal activities of an elderly person were used to train a Gaussian Mixture Model (GMM) to detect any abnormal event. Our method was tested with a realistic video data set of simulated falls and normal activities.
520 $a However, 3D information like the spatial localization of a person in a room can be very useful for action recognition. Although a multi-camera system is usually preferable to acquire 3D information, we have demonstrated that, with only one calibrated camera, it is possible to localize a person in his/her environment using the person's head. Concretely, the head, modeled by a 3D ellipsoid, was tracked in the video sequence using particle filters. The precision of the 3D head localization was evaluated with a video data set containing the real 3D head localizations obtained with a Motion Capture system. An application example using the 3D head trajectory for fall detection is also proposed.
520 $a In conclusion, we have confirmed that a video surveillance system for fall detection with only one camera per room is feasible. To reduce the risk of false alarms, a hybrid method combining 2D and 3D information could be considered.
520 $a Keywords. computer vision, videosurveillance, fall detection, motion detection, tracking, shape analysis, 3D localization.
590 $a School code: 0992.
650 4 $a Gerontology. $3 533633
650 4 $a Information Technology. $3 1030799
650 4 $a Health Sciences, Public Health. $3 1017659
650 4 $a Computer Science. $3 626642
690 $a 0351
690 $a 0489
690 $a 0573
690 $a 0984
710 2 $a Universite de Montreal (Canada). $3 1018132
773 0 $t Dissertation Abstracts International $g 72-01B.
790 $a 0992
791 $a Ph.D.
792 $a 2010
793 $a French
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=NR67195