Accelerating YOLO-based Real-time Object Detection via Foveated Rendering
Kimleang Kea, Sanghyeon Lee, Myeongjin Kwak, Youngsun Han · 2023
Foveated rendering emulates human vision by prioritizing sharpness at the center while introducing peripheral blur outside this central area. We explore its potential for enhancing object detection performance by integrating it into various object detection methods. Our investigation demonstrates that foveated rendering effectively reduces detection time and false alarm detections, thus showcasing its utility in improving object detection performance. Experimental results indicate a reduction in detection time of up to 20% compared with object detection using conventional rendering techniques.