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http://dx.doi.org/10.12673/jkoni.2012.16.2.386

Real-time Multi-Objects Recognition and Tracking Scheme  

Kim, Dae-Hoon (School of Electrical Engineering, Korea University)
Rho, Seung-Min (Division of Information and Communication, Baekseok University)
Hwang, Een-Jun (School of Electrical Engineering, Korea University)
Publication Information
Journal of Advanced Navigation Technology / v.16, no.2, 2012 , pp. 386-393 More about this Journal
Abstract
In this paper, we propose an efficient multi-object recognition and tracking scheme based on interest points of objects and their feature descriptors. To do that, we first define a set of object types of interest and collect their sample images. For sample images, we detect interest points and construct their feature descriptors using SURF. Next, we perform a statistical analysis of the local features to select representative points among them. Intuitively, the representative points of an object are the interest points that best characterize the object. in addition, we make the movement vectors of the interest points based on matching between their SURF descriptors and track the object using these vectors. Since our scheme treats all the objects independently, it can recognize and track multiple objects simultaneously. Through the experiments, we show that our proposed scheme can achieve reasonable performance.
Keywords
Object recognition; Object tracking; Real-time; Local feature descriptor;
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