We describe the functional and architectural breakdown of a monocular pedestrian detection system. We describe in detail our approach for single-frame classification based on a novel scheme of breaking down the class variability by repeatedly training a set of relatively simple classifiers on clusters of the training set. Single-frame classification performance results and system level performance figures for daytime conditions are presented with a discussion about the remaining gap to meet a daytime normal weather condition production system.
|Number of pages
|Published - 2004
|2004 IEEE Intelligent Vehicles Symposium - Parma, Italy
Duration: 14 Jun 2004 → 17 Jun 2004
|2004 IEEE Intelligent Vehicles Symposium
|14/06/04 → 17/06/04