Indoor Human Detection using RGB-D images
文献类型：会议论文
| 作者 | Wei Xia; Huiyun Li; Baopu Li; Haoyang Jin; Qi Zhang |
| 出版日期 | 2016 |
| 会议名称 | ICIA 2016 |
| 会议地点 | 浙江宁波 |
| 英文摘要 | Recently, RGB-D sensors such as Kinect and Xtion have received considerable attention since they provide depth image that is robust to light variation in the environment. They are mainly used for human computer interaction, surveillance and so on. In this paper, we concentrate on indoor human detection using RGB-D images. Some RGB image based features such as histogram of oriented gradient (HOG) and local binary pattern (LBP) are first briefly introduced. Then, a new depth feature that describes the self-similarity of an image is proposed. Finally, combination of them is utilized to detect the people. This scheme can efficiently describe the humans in the indoor environment. Extensive experiments demonstrate that the proposed scheme can achieve a respective promising detection accuracy of 99.28%, 95.48% and 99.91% on three different collected RGB-D data sets. |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/10078]  |
| 专题 | 深圳先进技术研究院_集成所 |
| 作者单位 | 2016 |
| 推荐引用方式 GB/T 7714 | Wei Xia,Huiyun Li,Baopu Li,et al. Indoor Human Detection using RGB-D images[C]. 见:ICIA 2016. 浙江宁波. |
入库方式： OAI收割
来源：深圳先进技术研究院
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