This paper studies the effects of front-end imager parameters on objectdetection performance and energy consumption. A custom version of histograms of oriented gradient (HOG) features based on 2-b pixel ratios is pre...
详细信息
This paper studies the effects of front-end imager parameters on objectdetection performance and energy consumption. A custom version of histograms of oriented gradient (HOG) features based on 2-b pixel ratios is presented and shown to achieve superior objectdetection performance for the same estimated energy compared with conventional HOG features. A front-end hardware implementation capable of extracting these features at multiple scales is proposed, and a system-level energy analysis is performed. This energy analysis suggests a potential 19x reduction in I/O energy and a 3.3x reduction in back-end detection energy compared with conventional objectdetection pipelines.
暂无评论