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Comparing features for target tracking in traffic scenes

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Published in Pattern Recognition. 1996, vol. 29, no. 8, p. 1285-1296
Abstract This paper describes a motion-analysis system, applied to the problem of vehicle tracking in real-world highway scenes. In a first stage a motion-detection algorithm performs a figure/ground segmentation, providing binary masks of the moving objects. In the second stage, vehicles are tracked by using Kalman filters for two state vectors, which represent each target's position and velocity. Three types of features have been used: (i) the bounding rectangle, (ii) the centroid of the convex polygon approximating the vehicles contour and (iii) the 2-D pattern of the vehicle. For each feature, the performance of the tracking algorithm has been tested in terms of robustness and computing time.
Keywords Motion detectionTrackingTraffic scenesKalman filterFeature comparison
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Research groups Computer Vision and Multimedia Laboratory
Multimodal Interaction Group
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GIL MILANESE, Sylvia, MILANESE, Ruggero, PUN, Thierry. Comparing features for target tracking in traffic scenes. In: Pattern Recognition, 1996, vol. 29, n° 8, p. 1285-1296. https://archive-ouverte.unige.ch/unige:47445

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Deposited on : 2015-03-03

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