DocumentCode
2866462
Title
Fall detection with depth-videos
Author
Aslan, Muzaffer ; Alcin, Omer Faruk ; Sengur, Abdulkadir ; Ince, Melih Cevdet
Author_Institution
Gazi Endustri Meslek Lisesi, Elektron. Bolumu, Elazığ, Turkey
fYear
2015
fDate
16-19 May 2015
Firstpage
443
Lastpage
446
Abstract
Elderly people, who are living alone are great risk if a fall event occurred. Therefore automatic fall detection systems are in demand for elderly people. In this paper, a depth based fall detection system is proposed. The proposed method consists of shape based fall characterization and a Support Vector Machine (SVM) classifier. Shape based fall characterization is formed with Curvature Scale Space (CSS) features and Fisher Vector (FV) encoding. According to the results obtained from experimental study, the proposed method has better performance than other methods that were published in literature.
Keywords
computational geometry; geriatrics; image classification; object detection; support vector machines; vectors; CSS features; FV encoding; Fisher vector encoding; SVM classifier; automatic fall detection systems; curvature scale space features; depth-videos; elderly people; shape based fall characterization; support vector machine classifier; Conferences; Encoding; Feature extraction; Informatics; Senior citizens; Shape; Support vector machines; Curvature scale space; Fall decection; Fisher vector; Support vector machines;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing and Communications Applications Conference (SIU), 2015 23th
Conference_Location
Malatya
Type
conf
DOI
10.1109/SIU.2015.7129854
Filename
7129854
Link To Document