Tracking of Multiple objects Using 3D Scatter Plot Reconstructed by Linear Stereo Vision

This paper presents a new method for tracking objects using stereo vision with linear cameras. Edge points extracted from the stereo linear images are first matched to reconstruct points that represent the objects in the scene. To detect the objects, a clustering process based on a spectral analysis is then applied to the reconstructed points. The obtained clusters are finally tracked throughout their center of gravity using Kalman filter and a Nearest Neighbour based data association algorithm. Experimental results using real stereo linear images are shown to demonstrate the effectiveness of the proposed method for obstacle tracking in front of a vehicle.

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