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http://dx.doi.org/10.7840/KICS.2011.36C.7.421

Real-time Recognition and Tracking System of Multiple Moving Objects  

Park, Ho-Sik (오산대학교 디지털전자과)
Bae, Cheol-Soo (관동대학교 전자통신공학과)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.36, no.7C, 2011 , pp. 421-427 More about this Journal
Abstract
The importance of the real-time object recognition and tracking field has been growing steadily due to rapid advancement in the computer vision applications industry. As is well known, the mean-shift algorithm is widely used in robust real-time object tracking systems. Since the mentioned algorithm is easy to implement and efficient in object tracking computation, many say it is suitable to be applied to real-time object tracking systems. However, one of the major drawbacks of this algorithm is that it always converges to a local mode, failing to perform well in a cluttered environment. In this paper, an Optical Flow-based algorithm which fits for real-time recognition of multiple moving objects is proposed. Also in the tests, the newly proposed method contributed to raising the similarity of multiple moving objects, the similarity was as high as 0.96, up 13.4% over that of the mean-shift algorithm. Meanwhile, the level of pixel errors from using the new method keenly decreased by more than 50% over that from applying the mean-shift algorithm. If the data processing speed in the video surveillance systems can be reduced further, owing to improved algorithms for faster moving object recognition and tracking functions, we will be able to expect much more efficient intelligent systems in this industrial arena.
Keywords
Object Recognition; Object Tracking; Optical Flow; Mean-shift Algorithm; Computer Vision;
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