Online Selection of Discriminative Pixel-Pair Feature for Tracking

K. Nishida, T. Kurita, and M. Higashikubo (Japan)


Visual Tracking, Discriminative Tracking, Online Feature Selection, Intelligent Traffic System


A novel visual tracking algorithm is proposed in this paper. The algorithm plays an important role in a cooperative driving support system (DSSS) that is aimed at reducing traffic fatalities and injuries. The input to the algorithm is a gray-scale image for every video frame from a roadside camera, and the algorithm can be used to detect the existence of vehicles on the road and then track their trajectories. In this algorithm, discriminative pixel-pair feature selection is adopted to discriminate between an image patch with an object in the correct position and image patches with objects in an incorrect position. The proposed algorithm showed stable and precise tracking performance when implemented in various illumination conditions and traffic conditions; the performance was especially good for the low-contrast vehicles running against a high-contrast background.

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