Shape Preserving RGB-D Depth Map Restoration

被引:0
|
作者
Liu, Wei [1 ]
Xue, Haoyang [1 ]
Gu, Yun [1 ]
Yang, Jie [1 ]
Wu, Qiang [2 ]
Jia, Zhenhong [3 ]
机构
[1] Shanghai Jiao Tong Univ, Minist Educ Syst Control & Informat Proc, Key Lab, Shanghai 200030, Peoples R China
[2] Univ Technol, Sch Comp & Communicat, Sydney, NSW, Australia
[3] Xinjiang Univ, Sch Informat Sci & Engn, Urumqi, Peoples R China
关键词
depth map restoration; joint bilateral filter; diffusion; Kinect;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The RGB-D cameras have enjoined a great popularity these years. However, the quality of the depth maps obtained by such cameras is far from perfect. In this paper, we propose a framework for shape preserving depth map restoration for RGB-D cameras. The quality of the depth map is improved from three aspects: 1) the proposed region adaptive bilateral filter (RA-BF) smooths the depth noise across the depth map adaptively, 2) by associating the color information with the depth information, incorrect depth values are adjusted properly, 3) a selective joint bilateral filter (SJBF) is proposed to successfully fill in the holes caused by low quality depth sensing. Encouraging performance is obtained through our experiments.
引用
收藏
页码:150 / 158
页数:9
相关论文
共 50 条
  • [1] RGB-D depth-map restoration using smooth depth neighborhood supports
    Liu, Wei
    Xue, Haoyang
    Yu, Zhongjie
    Wu, Qiang
    Yang, Jie
    [J]. JOURNAL OF ELECTRONIC IMAGING, 2015, 24 (03)
  • [2] Motion-Depth: RGB-D Depth Map Enhancement with Motion and Depth in Complement
    Hui, Tak-Wai
    Ngan, King Ngi
    [J]. 2014 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2014, : 3962 - 3969
  • [3] Depth Map Characterization of RGB-D Sensor for Obstacle Detection System
    Rivera, Xyza Vada Maree L.
    Cadubla, Ruel Mark D.
    Alemania, Jaymark M.
    Valdellon, Raniel E.
    Villanueva, Rinzi Rae Q.
    Vicerra, Ryan Rhay P.
    Roxas, Edison A.
    Dela Cruz, Angelo R.
    [J]. 2015 INTERNATIONAL CONFERENCE ON HUMANOID, NANOTECHNOLOGY, INFORMATION TECHNOLOGY,COMMUNICATION AND CONTROL, ENVIRONMENT AND MANAGEMENT (HNICEM), 2015, : 549 - +
  • [4] RGB-D Map for Robot Navigation
    Duchon, Frantisek
    Toelgyessy, Michal
    Chovanec, L'ubos
    Paszto, Peter
    Babinec, Andrej
    Gardian, Pavol
    [J]. 2014 ELEKTRO, 2014, : 154 - 158
  • [5] High-Quality Depth Map Upsampling and Completion for RGB-D Cameras
    Park, Jaesik
    Kim, Hyeongwoo
    Tai, Yu-Wing
    Brown, Michael S.
    Kweon, In So
    [J]. IEEE TRANSACTIONS ON IMAGE PROCESSING, 2014, 23 (12) : 5559 - 5572
  • [6] SUPERPIXEL-BASED DEPTH MAP INPAINTING FOR RGB-D VIEW SYNTHESIS
    Buyssens, P.
    Daisy, M.
    Tschumperle, D.
    Lezoray, O.
    [J]. 2015 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), 2015, : 4332 - 4336
  • [7] DEPTH MAP ENHANCEMENT ON RGB-D VIDEO CAPTURED BY KINECT V2
    Lin, Ke-Yu
    Hang, Hsueh-Ming
    [J]. 2018 ASIA-PACIFIC SIGNAL AND INFORMATION PROCESSING ASSOCIATION ANNUAL SUMMIT AND CONFERENCE (APSIPA ASC), 2018, : 1530 - 1535
  • [8] Depth Map Super-Resolution for Cost-Effective RGB-D Camera
    Takaoka, Ryotaro
    Hashimoto, Naoki
    [J]. 2015 INTERNATIONAL CONFERENCE ON CYBERWORLDS (CW), 2015, : 133 - 136
  • [9] Modeling deviations of rgb-d cameras for accurate depth map and color image registration
    Song, Xibin
    Zheng, Jianmin
    Zhong, Fan
    Qin, Xueying
    [J]. MULTIMEDIA TOOLS AND APPLICATIONS, 2018, 77 (12) : 14951 - 14977
  • [10] Modeling deviations of rgb-d cameras for accurate depth map and color image registration
    Xibin Song
    Jianmin Zheng
    Fan Zhong
    Xueying Qin
    [J]. Multimedia Tools and Applications, 2018, 77 : 14951 - 14977