DocumentCode :
595060
Title :
Camera view usage of binary infrared sensors for activity recognition
Author :
Shuai Tao ; Kudo, Motoi ; Nonaka, Hirofumi ; Toyama, Jun
Author_Institution :
Div. of Comput. Sci., Hokkaido Univ., Sapporo, Japan
fYear :
2012
fDate :
11-15 Nov. 2012
Firstpage :
1759
Lastpage :
1762
Abstract :
A ceiling sensor system is reported in this study to recognize different activities of multiple persons in the home environment. The sensors output binary sequences by which we know the existence/nonexistence of persons under the sensors. A short-period average of the binary response is shown to be regarded as a pixel value of a top view camera, but the camera-like view is more advantage in the sense of preserving privacy. Using the ”pixel values” as features, support vector machine (SVM) classifier succeeded to recognize eight activities of five subjects at average recognition rate of 80.10%. This accuracy is not sufficient in general but surprisingly high with such low-level information.
Keywords :
cameras; data privacy; home computing; image classification; image recognition; image sensors; image sequences; infrared detectors; support vector machines; SVM classifier; activity recognition; average recognition rate; binary infrared sensors; binary response; binary sequences; camera-like view; ceiling sensor system; home environment; pixel value; privacy preservation; short-period average; support vector machine classifier; top view camera; Cameras; Humans; Legged locomotion; Privacy; Sensors; Support vector machines; TV;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location :
Tsukuba
ISSN :
1051-4651
Print_ISBN :
978-1-4673-2216-4
Type :
conf
Filename :
6460491
Link To Document :
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