FPGAbased Accurate Pedestrian Detection with Thermal Camera for Surveillance System A surveillance system requires to achieve high accuracy of object detection at all times and to meet realtime processing requirements (30 frames per second) with high energyefficiency. Since thermal cameras allow to see even in darkness unlike a RGB camera, object detection with a thermal camera obtains higher accuracy in the night, and thereby it has attracted much attention. However, since it is challenging to extract informative features from a thermal image, implementation challenges of an object detection with high accuracy remain. To meet the requirements, we present a sparse YOLOv2based pedestrian detector with a thermal camera on an FPGA. For high accuracy, we propose a preprocessing that concatenates a thermal image with the background subtracted one for a detector to extract more informative features. Also, we develop a zero weight skipping architecture dedicated to our detector that contains a vectorizing unit that packs successive valid values into the same memory address to realize high parallel degree calculation. It leads to meet the realtime processing requirement with high energyefficiency. Compared with a conventional one, Fscore was 29 points higher, and speed was 3.3 times faster. Therefore, our system is more suitable for surveillance systems.

FPGABased Object Detection for Autonomous Driving System Autonomous driving systems require a realtime detection of the objects including pedestrians and obstacles on the roads. Object detection by image processing is a popular approach for autonomous driving systems. However, there are complex reflections caused by multiple light sources and objects on the roads, which disturb the robust and realtime object detection. This paper describes an FPGAbased object detection method for autonomous driving systems using multiple CMOS cameras. Our system is implemented on Xilinx Zynq7020 SoCFPGA, in which realtime processing of tracking whitelines for lanekeeping and obstaclespedestrians detection on the roads are executed by the hardware on the Programmable Logics, and the whole system is controlled by a software on the Processing System (CPU) written in Python language.