Background-aware pedestrian/vehicle detection system for driving environments

In this paper, we introduce the new approach to enhance the reliability of detection of objects in a driving environment (e.g. pedestrian and vehicle). We present the method of filtering out false positive detections while maintaining true positive detections. Our approach considers that if we remove a certain region from an image taken from a vehicle in a driving environment, the inpainting algorithm is able to restore the removed region based on its surroundings when it does not include objects. Previous inpainting algorithms were used for restoration of damaged paintings, and we expand its usage to confirm whether the detection result includes the real object or not. Furthermore, we introduce a simple but effective speedup method for the sliding window using simple edge features of objects. Experimental results confirm that our approach is able to improve the accuracies of various pedestrian and vehicle detectors. We show the improved accuracy of pedestrian and vehicle detection in a driving environment with various detectors.