Transition: A Relevant Image Feature for Fast Obstacle Detection.

Currently, the automotive industry is actively seeking generic obstacle sensors based on monocular vision that are able to run on low frequency central processing units (CPUs). The authors have tackled the challenge of designing a vision-based obstacle detection system using a common in-vehiclemicro controller: an 80 MHz 32 bits RISC CPU. This system uses a single wide angle rear camera commercially available. To insure real-time obstacledetection, we proposed a novel fast feature-point extractor applied alonga 1D signal. The authors named it transition. It is 100 times faster thanHarris and relevant on man-made objects. The authors present feature extraction results and demonstrate that it can be used to detect various typesof obstacles with an 80MHz CPU.