摘要
An ARM-platform and FPGA-based accelerator rather than PC-based system is utilized in this study for completing a real-time FPGA-based human detector. The system presents the advantages of small size, low cost, high computing speed, and being portable and could be built in small cameras for surveillance applications. When background segmentation is introduced, the computing efficiency could reach about 15 fps. Moreover, this study has proven that the reduction on the total detection rate is less than 0.3% while changing HOG algorithm into the presented FPGA hardware implementation.
原文 | 英語 |
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主出版物標題 | Proceedings - 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016 |
發行者 | Institute of Electrical and Electronics Engineers Inc. |
頁面 | 1014-1017 |
頁數 | 4 |
ISBN(電子) | 9781509030712 |
DOIs | |
出版狀態 | 已出版 - 16 08 2016 |
對外發佈 | 是 |
事件 | 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016 - Xi'an, 中國 持續時間: 04 07 2016 → 06 07 2016 |
出版系列
名字 | Proceedings - 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016 |
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Conference
Conference | 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016 |
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國家/地區 | 中國 |
城市 | Xi'an |
期間 | 04/07/16 → 06/07/16 |
文獻附註
Publisher Copyright:© 2016 IEEE.