Towards a Human-like Vision System for Resource-Constrained Intelligent Cars

Abstract

Research on computer vision systems for driver assistance resulted in a variety of approaches mainly performing reactive tasks like, e.g., lane keeping. However, for a full understanding of generic traffic situations, integrated and more flexible approaches are needed. We present a system inspired by the human visual system. Based on combining task-dependent tunable visual saliency, an object recognizer, and a tracker it provides warnings in dangerous situations.