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Object Detection and Tracking in Range Image Sequences by Separation of Image Features

E.B. Meier and F. Ade
Proceedings of the IEEE International Conference on Intelligent Vehicles
1998

Abstract

We propose a new approach for a driver assistance system based on range image sequences to increase the safety on motorways. This control system is capable of automatically keeping the car at an adequate distance or warning the driver when he gets too close to other cars. The knowledge of the sensor geometry with respect to the road is used to separate image features into ground and road obstacles. We assume that the road is flat but possibly inclined. To distinguish between obstacles and road pixels we use a separating plane that is slightly steeper than the current road model. Pixels lying above this plane are assumed to belong to obstacles, and pixels below the plane are assumed to belong to the road. To update the road model, we fit a plane through all pixels marked as ground. The partition of the detected obstacles into their different objects is performed using connected component analysis. Components are then merged into objects according to proximity. For the tracking we employ Kalman filtering to provide most likely estimates of the state of each object. We show results of some experiments with simulated traffic scenes and toy traffic scenarios. Real data will be available later in the project.


Download in postscript format
@InProceedings{eth_biwi_00138,
  author = {E.B. Meier and F. Ade},
  title = {Object Detection and Tracking in Range Image Sequences by Separation of Image Features},
  booktitle = {Proceedings of the IEEE International Conference on Intelligent Vehicles},
  year = {1998},
  pages = {176-181},
  keywords = {range data, segmentation, model-based, tracking}
}