A Scalable, High-Performance Motion Estimation Application for a Weakly-Programmable FPGA Architecture

Computer architectures for advanced driver assistance systems have become increasingly important in the automotive industry. They target safety-critical applications, which process large amounts of incoming sensor data. This is especially the case for image processing applications, which must handle several uncompressed image streams from multiple cameras. As one possible target architecture, FPGAs provide sufficient processing power for complex applications such as lane or object detection. A particularly challenging application is the reliable detection of moving objects, which is the basis for several future driver assistance applications, such as a digital 3D reconstruction of a vehicle's surroundings. This paper presents an advanced Motion Estimation application, which achieves high performance processing of up to 449 FPS for an image resolution of 512 × 384 pixels. The implementation concept relies on weakly-programmable processing elements and a reconfigurable data path, which allows an efficient exploitation of the FPGA's chip area and clock frequencies, leading to a flexible solution that fits future application requirements.