Depth Maps Restoration for Human Using RealSense

doi:10.1109/ACCESS.2019.2934863

CORC > 计算技术研究所 > 中国科学院计算技术研究所 > 中国科学院计算技术研究所期刊论文 > 英文

	Depth Maps Restoration for Human Using RealSense
	Yin, Jingfang 2; Zhu, Dengming 2; Shi, Min 1; Wang, Zhaoqi 2
刊名	IEEE ACCESS
	2019
卷号	7 页码:112544-112553
关键词	RGBD camera human depth map restoration two-stage stacked hourglass network register and measure human 3D models
ISSN号	2169-3536
DOI	10.1109/ACCESS.2019.2934863
英文摘要	Recently, mobile devices such as iPhone X start to be equipped with depth cameras, and more applications based on captured depth maps are emerging. Among many depth cameras on the market, Intel RealSense has the ability to capture depth information and is expected to be widely used in mobile devices and laptops. However, depth maps captured by RealSense always suffer from severe holes and noises, which make it hard to be used in real applications. In this paper, we propose a method to fill holes and remove noises in depth maps captured by RealSense. This method includes two parts: human depth prediction and human depth optimization. Firstly, we propose a two-stage stacked hourglass network to predict human part-segmentation and human depth simultaneously based on RGB image. Then we use GradientFMM method to optimize captured depth maps with the guidance of the above human depth prediction. The RGB image and depth maps mentioned above are captured by the same RealSense device. Furthermore, in order to show the effectiveness of the proposed method, we register and measure human 3D models based on optimized depth maps. The experimental results show that our method can restore depth maps for human using RealSense effectively.
资助项目	National Science and Technology Major Project[2017ZX05019005] ; National Natural Science Foundation of China[61532002] ; Taicang Technology Project[TC2017DYDS07]
WOS研究方向	Computer Science ; Engineering ; Telecommunications
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000484306100001
内容类型	期刊论文
源URL	[http://119.78.100.204/handle/2XEOYT63/4698]
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Zhu, Dengming
作者单位	1.North China Elect Power Univ, Sch Control & Comp Engn, Beijing 102206, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Yin, Jingfang,Zhu, Dengming,Shi, Min,et al. Depth Maps Restoration for Human Using RealSense[J]. IEEE ACCESS,2019,7:112544-112553.
APA	Yin, Jingfang,Zhu, Dengming,Shi, Min,&Wang, Zhaoqi.(2019).Depth Maps Restoration for Human Using RealSense.IEEE ACCESS,7,112544-112553.
MLA	Yin, Jingfang,et al."Depth Maps Restoration for Human Using RealSense".IEEE ACCESS 7(2019):112544-112553.