Knowledge Commons of Institute of Automation,CAS
Feature Enhancement for Joint Human and Head Detection | |
Zhang, Yongming1,2; Zhang, Shifeng1,2; Zhuang, Chubin1,2; Lei, Zhen1,2 | |
2019 | |
会议名称 | CCF Chinese Conference Biometric Recognition |
会议日期 | 2019 |
会议地点 | 湖南湘潭 |
摘要 | Human and head detection have been rapidly improved with the development of deep convolutional neural networks. However, these two detection tasks are often studied separately, without taking advantage of the relationship between human and head. In this paper, we present a new two-stage detection framework, namely Joint Enhancement Detection (JED), to simultaneously detect human and head based on enhanced features. Specifically, the proposed JED contains two newly added modules, i.e., the Body Enhancement Module (BEM) and the Head Enhancement Module (HEM). The former is designed to enhance the features used for human detection, while the latter aims to enhance the features used for head detection. With these enhanced features in a joint framework, the proposed method is able to detect human and head simultaneously and efficiently. We verify the effectiveness of the proposed method on the CrowdHuman dataset and achieve better performance than baseline method for both human and head detection. |
收录类别 | EI |
语种 | 英语 |
七大方向——子方向分类 | 图像视频处理与分析 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/39053 |
专题 | 多模态人工智能系统全国重点实验室_生物识别与安全技术 |
作者单位 | 1.Institute of Automation Chinese Academy of Sciences 2.University of Chinese Academy of Sciences |
第一作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Zhang, Yongming,Zhang, Shifeng,Zhuang, Chubin,et al. Feature Enhancement for Joint Human and Head Detection[C],2019. |
条目包含的文件 | 条目无相关文件。 |
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