12,000-fps Multi-object Detection Using HOG Descriptor and SVM Classifier
文献类型：会议论文
| 作者 | Li Jianquan1,2 ; Yin Yingjie1,2; Liu Xilong1,2; Xu De1,2; Gu Qingyi1,2
|
| 出版日期 | 2017-09 |
| 会议日期 | September 24–28, 201 |
| 会议地点 | Vancouver, BC, Canada |
| 英文摘要 | Abstract— This paper describes a high-frame-rate (HFR) vision system that can detect multiple objects in an image of 512×512 pixels at 12,000 frames per seconds (fps). An optimized algorithm is proposed based on conventional Histograms of Oriented Gradient (HOG) descriptor and Support Vector Machine (SVM) classifier algorithms for hardware implementation. By implementing the proposed algorithm on a field-programmable gate array (FPGA) of a high-speed vision platform, multiobject in an image can be detected at 12,000 fps under complex background. In hardware implementation, 64 pixels were processed in parallel with 80 MHz camera clock. Source image and detection results can be transferred to personal computer (PC) in real-time for recording or post-processing. Our developed HFR multi-object detection system was verified by performing several evaluations. |
| 源URL | [http://ir.ia.ac.cn/handle/173211/20064]  |
| 专题 | 精密感知与控制研究中心_精密感知与控制 中国科学院自动化研究所 |
| 作者单位 | 1.CASIA 2.UCAS |
| 推荐引用方式 GB/T 7714 | Li Jianquan,Yin Yingjie,Liu Xilong,et al. 12,000-fps Multi-object Detection Using HOG Descriptor and SVM Classifier[C]. 见:. Vancouver, BC, Canada. September 24–28, 201. |
入库方式： OAI收割
来源：自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。