基于GPU的车载全景视觉系统

针对大、中型车辆在行驶、泊车过程中存在的视觉盲区以及多路视频全景拼接难以实时等工程化问题,本文设计出一种基于FPGA和GPU平台的多路相机安全驾驶辅助系统.FPGA实现图像数据采集、参数传递等预处理,在GPU上实现拼接算法的并行加速.在算法上优化实现多相机自动化标定,生成融合参数表以获取精确的融合配准关系.实验结果表明,该系统可适应多路鱼眼相机的实时拼接,在TX2上稳定的拼接速度可达到33 fps.

Vehicle Panoramic Vision System Based on GPU

Aiming at the engineering problems such as the blind spots of large and medium vehicles during driving and parking and the difficulty of multi-channel real-time video stitching, we design a safe driving assistance system based on multi-channel cameras as well as FPGA and GPU platforms. FPGA is responsible for preprocessing, including image data acquisition and parameter transfer, and parallel acceleration of stitching algorithms is enabled on GPU. Besides, automatic calibration of multiple cameras is achieved with the optimized algorithm, and a fusion parameter table was generated to acquire accurate image registration and fusion. The experimental results prove that the system can adapt to the real-time stitching of multi-channel fish-eye cameras, and the stable stitching speed on TX2 can reach 33 fps.