A Lightweight Pedestrian Detection Engine with Two-Stage Low-Complexity Detection Network and Adaptive Region Focusing Technique.

Pedestrian detection has been widely used in applications such as video surveillance and intelligent robots. Recently, deep learning-based pedestrian detection engines have attracted lots of attention. However, the computational complexity of these engines is high, which makes them unsuitable for hardware- and power-constrained mobile applications, such as drones for surveillance. In this paper, we propose a lightweight pedestrian detection engine with a two-stage low-complexity detection network and adaptive region focusing technique, to reduce the computational complexity in pedestrian detection, while maintaining sufficient detection accuracy. The proposed pedestrian detection engine has significantly reduced the number of parameters (0.73 M) and operations (1.04 B), while achieving a comparable precision (85.18%) and miss rate (25.16%) to many existing designs. Moreover, the proposed engine, together with YOLOv3 and YOLOv3-Tiny, has been implemented on a Xilinx FPGA Zynq7020 for comparison. It is able to achieve 16.3 Fps while consuming 0.59 W, which outperforms the results of YOLOv3 (5.3 Fps, 2.43 W) and YOLOv3-Tiny (12.8 Fps, 0.95 W).

A Biological Retina Inspired Tone Mapping Processor for High-Speed and Energy-Efficient Image Enhancement.

In this work, a biological retina inspired tone mapping processor for high-speed and energy-efficient image enhancement has been proposed. To achieve high throughput and high energy efficiency, several hardware design techniques have been proposed, including data partition based parallel processing with S-shape sliding, adjacent frame feature sharing, multi-layer convolution pipelining, and convolution filter compression with zero skipping convolution. Implemented on a Xilinx's Virtex7 FPGA, the proposed design achieves a high throughput of 189 frames per second for 1024 × 768 RGB images while consuming 819 mW. Compared with several state-of-the-art tone mapping processors, the proposed design shows higher throughput and energy efficiency. It is suitable for high-speed and energy-constrained image enhancement applications.