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.
Bibliographical noteFunding 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).
- Abnormality detection
- Dynamic group warping
- Dynamic view warping
- Motion sequence matching
- Smart spaces
- Surveillance camera
ASJC Scopus subject areas
- Computer Science Applications
- Electrical and Electronic Engineering