Human detection using motion and appearance based feature

Shaopeng Tang; Satoshi Goto

doi:10.1109/ICICS.2009.5397675

Human detection using motion and appearance based feature

Shaopeng Tang^*, Satoshi Goto

^*Corresponding author for this work

Waseda University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Citations (Scopus)

Abstract

An approach to detect moving and standing human from video is proposed in this paper. Human detection from videos is a difficult problem because of motion of human, camera and background. In order to detect moving human, the dense optical flow is calculated by two consecutive frames, to represent the motion of human. Motion based feature is extracted from optical flow field. It not only represents the global motion caused by the boundary of human body, but also contains local motion caused by the limbs. Motion based feature is combined with histogram of template feature, which is designed to detect standing human, as final feature for detection. Experiment on CAS dataset shows that this feature has more discriminative ability than other motion based feature. Besides, this feature is easier for hardware acceleration, which makes it suitable for real time application.

Original language	English
Title of host publication	ICICS 2009 - Conference Proceedings of the 7th International Conference on Information, Communications and Signal Processing
DOIs	https://doi.org/10.1109/ICICS.2009.5397675
Publication status	Published - 2009
Event	7th International Conference on Information, Communications and Signal Processing, ICICS 2009 - Macau Fisherman's Wharf Duration: 2009 Dec 8 → 2009 Dec 10

Other

Other	7th International Conference on Information, Communications and Signal Processing, ICICS 2009
City	Macau Fisherman's Wharf
Period	09/12/8 → 09/12/10

Keywords

Histogram of template
Human detection
Optical flow

ASJC Scopus subject areas

Computer Networks and Communications
Information Systems
Signal Processing

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10.1109/ICICS.2009.5397675

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Tang, S & Goto, S 2009, Human detection using motion and appearance based feature. in ICICS 2009 - Conference Proceedings of the 7th International Conference on Information, Communications and Signal Processing., 5397675, 7th International Conference on Information, Communications and Signal Processing, ICICS 2009, Macau Fisherman's Wharf, 09/12/8. https://doi.org/10.1109/ICICS.2009.5397675

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abstract = "An approach to detect moving and standing human from video is proposed in this paper. Human detection from videos is a difficult problem because of motion of human, camera and background. In order to detect moving human, the dense optical flow is calculated by two consecutive frames, to represent the motion of human. Motion based feature is extracted from optical flow field. It not only represents the global motion caused by the boundary of human body, but also contains local motion caused by the limbs. Motion based feature is combined with histogram of template feature, which is designed to detect standing human, as final feature for detection. Experiment on CAS dataset shows that this feature has more discriminative ability than other motion based feature. Besides, this feature is easier for hardware acceleration, which makes it suitable for real time application.",

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author = "Shaopeng Tang and Satoshi Goto",

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language = "English",

isbn = "9781424446575",

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note = "7th International Conference on Information, Communications and Signal Processing, ICICS 2009 ; Conference date: 08-12-2009 Through 10-12-2009",

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AU - Goto, Satoshi

PY - 2009

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N2 - An approach to detect moving and standing human from video is proposed in this paper. Human detection from videos is a difficult problem because of motion of human, camera and background. In order to detect moving human, the dense optical flow is calculated by two consecutive frames, to represent the motion of human. Motion based feature is extracted from optical flow field. It not only represents the global motion caused by the boundary of human body, but also contains local motion caused by the limbs. Motion based feature is combined with histogram of template feature, which is designed to detect standing human, as final feature for detection. Experiment on CAS dataset shows that this feature has more discriminative ability than other motion based feature. Besides, this feature is easier for hardware acceleration, which makes it suitable for real time application.

AB - An approach to detect moving and standing human from video is proposed in this paper. Human detection from videos is a difficult problem because of motion of human, camera and background. In order to detect moving human, the dense optical flow is calculated by two consecutive frames, to represent the motion of human. Motion based feature is extracted from optical flow field. It not only represents the global motion caused by the boundary of human body, but also contains local motion caused by the limbs. Motion based feature is combined with histogram of template feature, which is designed to detect standing human, as final feature for detection. Experiment on CAS dataset shows that this feature has more discriminative ability than other motion based feature. Besides, this feature is easier for hardware acceleration, which makes it suitable for real time application.

KW - Histogram of template

KW - Human detection

KW - Optical flow

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Human detection using motion and appearance based feature

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Keywords

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