中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 计算技术研究所
  3. 中国科学院计算技术研究所
  4. 中国科学院计算技术研究所期刊论文
  5. 英文
Joint Pedestrian and Body Part Detection via Semantic Relationship Learning

文献类型：期刊论文

作者Han, Hu2; Chen, Wenbai1; Gu, Junhua3,4; Lan, Chuanxin2,4
刊名APPLIED SCIENCES-BASEL
出版日期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
DOI10.3390/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
WOS记录号WOS:000460696500138
出版者MDPI
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.

入库方式： OAI收割

来源：计算技术研究所

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。