TY - JOUR
T1 - Motion sequence-based human abnormality detection scheme for smart spaces
AU - Tak, Yoon Sik
AU - Rho, Seungmin
AU - Hwang, Eenjun
N1 - Funding Information:
Acknowledgments This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2010-0025395) and the MKE (Ministry of Knowledge Economy), Korea, under the ITRC (Information Technology Research Center) support program supervised by the NIPA (National IT Industry Promotion Agency) (NIPA-2011-C1090-1101-0008).
PY - 2011/10
Y1 - 2011/10
N2 - Smart spaces represent an emerging new paradigm that encompasses diverse active research areas such as ubiquitous, grid and cloud computing. Hence, there are a wide variety of interesting issues and applications for smart spaces, and surveillance is one issue that has long received much attention. In many cases, human motion is one of the most important clues used in assessing a situation for surveillance purposes. In this paper, we propose a new human abnormality detection scheme for surveillance purposes. More specifically, we first present a motion sequence matching algorithm called Dynamic View Warping to represent specific motion characteristics. Secondly, we propose a matching speed-up technique called Dynamic Group Warping that establishes boundaries in Dynamic View Warping. Thirdly, we propose an indexing scheme for motion sequences and present K-NN search algorithm to efficiently and effectively find similar motion sequences. Our extensive experiments show that our proposed methods achieve outstanding performance.
AB - Smart spaces represent an emerging new paradigm that encompasses diverse active research areas such as ubiquitous, grid and cloud computing. Hence, there are a wide variety of interesting issues and applications for smart spaces, and surveillance is one issue that has long received much attention. In many cases, human motion is one of the most important clues used in assessing a situation for surveillance purposes. In this paper, we propose a new human abnormality detection scheme for surveillance purposes. More specifically, we first present a motion sequence matching algorithm called Dynamic View Warping to represent specific motion characteristics. Secondly, we propose a matching speed-up technique called Dynamic Group Warping that establishes boundaries in Dynamic View Warping. Thirdly, we propose an indexing scheme for motion sequences and present K-NN search algorithm to efficiently and effectively find similar motion sequences. Our extensive experiments show that our proposed methods achieve outstanding performance.
KW - Abnormality detection
KW - Dynamic group warping
KW - Dynamic view warping
KW - Motion sequence matching
KW - Smart spaces
KW - Surveillance camera
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U2 - 10.1007/s11277-011-0305-8
DO - 10.1007/s11277-011-0305-8
M3 - Article
AN - SCOPUS:80053566646
VL - 60
SP - 507
EP - 519
JO - Wireless Personal Communications
JF - Wireless Personal Communications
SN - 0929-6212
IS - 3
ER -