Presentation 2011-03-10
Abnormal Motion Detection Using Temporal and Spatial Information
Hisashi MIKADO, Kazunori ONOGUCHI,
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Abstract(in English) This paper presents a method to detect abnormal motion by using spatio-temporal features. At first, silhouette images obtained from the backgrouund subtraction are separated into the upper part and the lower part. Each part is separated into some blocks so that the number of pixels in each block may be distributed equally. Next, the fourier transform is applied to time series data consisting of the pixel density in each block and the motion features are detected. In addition to the motion features, the shape features are detected by calculating the mean and the variance of the pixel density in each block. The classifier using one class SVM is created by leaning feature vectors generated from this process. Our method can detect both dynamic abnormal motions and static ones. In this experiment, walking, running or stopping was detected as normal motion,and the others were abnormal. The validity of the method was confirmed by experimental results.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Abnormal Detection / Discrete Fourier Transform / One Class SVM
Paper # PRMU2010-257
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Conference Information
Committee PRMU
Conference Date 2011/3/3(1days)
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Paper Information
Registration To Pattern Recognition and Media Understanding (PRMU)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Abnormal Motion Detection Using Temporal and Spatial Information
Sub Title (in English)
Keyword(1) Abnormal Detection
Keyword(2) Discrete Fourier Transform
Keyword(3) One Class SVM
1st Author's Name Hisashi MIKADO
1st Author's Affiliation Faculty of Science and Technology, Hirosaki University()
2nd Author's Name Kazunori ONOGUCHI
2nd Author's Affiliation Faculty of Science and Technology, Hirosaki University
Date 2011-03-10
Paper # PRMU2010-257
Volume (vol) vol.110
Number (no) 467
Page pp.pp.-
#Pages 6
Date of Issue