Optimized Method for Real-time Texture Reconstruction with RGB-D Camera

被引:0
|
作者
Yonghong Hou
Hang Li
Chuankun Liu
Liang Zhang
机构
[1] School of Electrical and Information Engineering, Tianjin University
[2] Tianjin Lishen Battery Joint-Stock Co., Ltd
[3] Tianjin Key Laboratory of Advanced Electrical Engineering and Energy Technology, School of Electrical Engineering and Automation, Tianjin Polytechnic University
关键词
Real-time 3D reconstruction; RGB-D camera; Texture reconstruction; Blur detection;
D O I
暂无
中图分类号
TP391.41 [];
学科分类号
080203 ;
摘要
With the appearance of RGB-D camera, the field of three-dimensional(3D) reconstruction receives more and more attention. In this paper, we present an optimization approach to produce high-quality textured 3D models based on the real-time 3D reconstruction system.The resulting models of real-time texture reconstruction often suffer from blurring, ghosting, and other artifacts.Our approach addresses this texture quality problem using blur detection and an optimized weight function. Experimental results demonstrate that our approach can improve the quality of textured 3D models by reducing the blur and ghosts on the model surface.
引用
收藏
页码:493 / 500
页数:8
相关论文
共 50 条
  • [21] Surface Reconstruction for RGB-D Data using Real-Time Depth Propagation
    Varadarajan, Karthik Mahesh
    Vincze, Markus
    2011 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCV WORKSHOPS), 2011,
  • [22] Real-Time 3D Modeling with a RGB-D Camera and On-Board Processing
    Aguilar, Wilbert G.
    Rodriguez, Guillermo A.
    Alvarez, Leandro
    Sandoval, Sebastian
    Quisaguano, Fernando
    Limaico, Alex
    AUGMENTED REALITY, VIRTUAL REALITY, AND COMPUTER GRAPHICS, AVR 2017, PT II, 2017, 10325 : 410 - 419
  • [23] Detecting and tracking people in real time with RGB-D camera
    Liu, Jun
    Liu, Ye
    Zhang, Guyue
    Zhu, Peiru
    Chen, Yan Qiu
    PATTERN RECOGNITION LETTERS, 2015, 53 : 16 - 23
  • [24] TextureFusion: High-Quality Texture Acquisition for Real-Time RGB-D Scanning
    Lee, Joo Ho
    Ha, Hyunho
    Dong, Yue
    Tong, Xin
    Kim, Min H.
    2020 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2020, : 1269 - 1277
  • [25] Electroholography of real scenes by RGB-D camera and the downsampling method
    Hasegawa, Satoki
    Yanagihara, Hidenari
    Yamamoto, Yota
    Kakue, Takashi
    Shimobaba, Tomoyoshi
    Ito, Tomoyoshi
    OSA CONTINUUM, 2019, 2 (05) : 1629 - 1638
  • [26] Real-time bi-directional people counting using an RGB-D camera
    Rahmaniar, Wahyu
    Wang, W. J.
    Chiu, Chi-Wei Ethan
    Hakim, Noorkholis Luthfil Luthfil
    SENSOR REVIEW, 2021, 41 (04) : 341 - 349
  • [27] Real-time Visual Odometry for Autonomous MAV Navigation using RGB-D Camera
    Wang, Jiefei
    Garratt, Matthew
    Anavatti, Sreenatha
    Lin, Shanggang
    2015 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS (ROBIO), 2015, : 1353 - 1358
  • [28] Real-time Lane Marker Detection Using Template Matching with RGB-D Camera
    Cong Hoang Quach
    Van Lien Tran
    Duy Hung Nguyen
    Viet Thang Nguyen
    Minh Trien Pham
    Manh Duong Phung
    PROCEEDINGS OF 2018 2ND INTERNATIONAL CONFERENCE ON RECENT ADVANCES IN SIGNAL PROCESSING, TELECOMMUNICATIONS & COMPUTING (SIGTELCOM 2018), 2018, : 152 - 157
  • [29] Real-Time RGB-D Camera Relocalization via Randomized Ferns for Keyframe Encoding
    Glocker, Ben
    Shotton, Jamie
    Criminisi, Antonio
    Izadi, Shahram
    IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 2015, 21 (05) : 571 - 583
  • [30] Real-time Tracking-by-Detection of Human Motion in RGB-D Camera Networks
    Malaguti, Alessandro
    Carraro, Marco
    Guidolin, Mattia
    Tagliapietra, Luca
    Menegatti, Emanuele
    Ghidoni, Stefano
    2019 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC), 2019, : 3198 - 3204