Camera and laser range finder fusion for real-time car detection
Cáceres Hernández, Danilo
Hyun Jo, Kang
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This paper describes a car detection method by combining data obtained from a laser and a camera. Data from the camera and the laser range finder (LRF) are combined after a calibration method has been performed. The calibration method defines the relative pose between camera and LRF. Car candidates are then extracted from the LRF data. The car candidate regions on the image are generated based on the filtered LRF data based on its size. To filter out the bad candidates, a verification method is performed on the car candidate regions. This method eliminates the needs of checking over several positions and scales, enables a speed enhancement over the general object detection strategy.