Joint Pedestrian and Body Part Detection via Semantic Relationship Learning | |
Han, Hu2; Chen, Wenbai1; Gu, Junhua3,4; Lan, Chuanxin2,4 | |
刊名 | APPLIED SCIENCES-BASEL |
2019-02-02 | |
卷号 | 9期号:4页码:14 |
关键词 | joint pedestrian and body part detection adaptive joint non-maximum suppression semantic relationship learning |
ISSN号 | 2076-3417 |
DOI | 10.3390/app9040752 |
英文摘要 | While remarkable progress has been made to pedestrian detection in recent years, robust pedestrian detection in the wild e.g., under surveillance scenarios with occlusions, remains a challenging problem. In this paper, we present a novel approach for joint pedestrian and body part detection via semantic relationship learning under unconstrained scenarios. Specifically, we propose a Body Part Indexed Feature (BPIF) representation to encode the semantic relationship between individual body parts (i.e., head, head-shoulder, upper body, and whole body) and highlight per body part features, providing robustness against partial occlusions to the whole body. We also propose an Adaptive Joint Non-Maximum Suppression (AJ-NMS) to replace the original NMS algorithm widely used in object detection, leading to higher precision and recall for detecting overlapped pedestrians. Experimental results on the public-domain CUHK-SYSU Person Search Dataset show that the proposed approach outperforms the state-of-the-art methods for joint pedestrian and body part detection in the wild. |
资助项目 | NSF of Hebei Province through the Key Program[F2016202144] |
WOS研究方向 | Chemistry ; Materials Science ; Physics |
语种 | 英语 |
出版者 | MDPI |
WOS记录号 | WOS:000460696500138 |
内容类型 | 期刊论文 |
源URL | [http://119.78.100.204/handle/2XEOYT63/4115] |
专题 | 中国科学院计算技术研究所期刊论文_英文 |
通讯作者 | Han, Hu |
作者单位 | 1.Beijing Informat Sci & Technol Univ, Sch Automat, Beijing 100101, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China 3.Hebei Prov Key Lab Big Data Comp, Tianjin 300401, Peoples R China 4.Hebei Univ Technol, Sch Artificial Intelligence, Tianjin 300401, Peoples R China |
推荐引用方式 GB/T 7714 | Han, Hu,Chen, Wenbai,Gu, Junhua,et al. Joint Pedestrian and Body Part Detection via Semantic Relationship Learning[J]. APPLIED SCIENCES-BASEL,2019,9(4):14. |
APA | Han, Hu,Chen, Wenbai,Gu, Junhua,&Lan, Chuanxin.(2019).Joint Pedestrian and Body Part Detection via Semantic Relationship Learning.APPLIED SCIENCES-BASEL,9(4),14. |
MLA | Han, Hu,et al."Joint Pedestrian and Body Part Detection via Semantic Relationship Learning".APPLIED SCIENCES-BASEL 9.4(2019):14. |
个性服务 |
查看访问统计 |
相关权益政策 |
暂无数据 |
收藏/分享 |
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。
修改评论