Real-Time Pedestrian Recognition in Urban Environments

Traditionally, pedestrian recognition is a great research topic in computer vision applied to advanced driver assistance systems ( ADAS); a real-time pedestrian recognition system based on stereo vision is presented in this paper. The most interesting features of the system are that it does not need any extrinsic calibration and it is possible to determine the pedestrian’s localization with a bigger resolution than only by using the disparity values. This is possible because the road profile in front of the vehicle is calculated from the v-disparity at each frame. Once the road profile has been generated the obstacles can be classified into elevated obstacles or obstacles on the ground. Regarding the pedestrian recognition, a fast method has been developed based on the similarity between the vertical projection of the pedestrian’s silhouette and a normal distribution. Stereo algorithms have a high computation time and in order to cope with this, our algorithm has been implemented in graphics processing unit by means of CUDA.