Helping Driverless Cars Detect Pedestrians

The pedestrian detection system developed in the Statistical Visual Computing Lab at UC San Diego. An advanced pedestrian detection system has been demonstrated to perform at two to four frames per second, achieving almost real-time recognition.This was accomplished by incorporating deep learning algorithms into a cascade detection program. “We’re aiming to build computer vision systems that will help computers better understand the world around them,” said research director Nuno Vasconcelos. “A big goal is real-time vision especially for pedestrian detection systems in self-driving cars.” New Algorithm with Deep Learning Models The new pedestrian detection algorithm breaks an image down into small windows for processing by a classifier, which signals whether a pedestrian is present or not. Since pedestrians appear in different sizes depending on the camera’s distance, millions of windows are…


Link to Full Article: Helping Driverless Cars Detect Pedestrians