Spatio-temporal fusion of multiple view video rate 3D surfaces

被引:1
|
作者
Collins, G [1 ]
Hilton, A [1 ]
机构
[1] Univ Surrey, Ctr Speech Vis & Signal Proc, Guildford GU2 5XH, Surrey, England
关键词
D O I
10.1109/3DIM.2005.75
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
We consider the problem of geometric integration and representation of multiple views of non-rigidly deforming 3D surface geometry captured at video rate. Instead of treating each frame as a separate mesh we present a representation which takes into consideration temporal and spatial coherence in the data where possible. We first segment gross base transformations using correspondence based on a closest point metric and represent these motions as piecewise rigid transformations. The remaining residual is encoded as displacement maps at each frame giving a displacement video. At both these stages occlusions and missing data are interpolated to give a representation which is continuous in space and time. We demonstrate the integration of multiple views for four different non-rigidly deforming scenes: hand, face, cloth and a composite scene. The approach achieves the integration of multiple-view data at different times into one representation which can processed and edited.
引用
收藏
页码:142 / 149
页数:8
相关论文
共 50 条
  • [41] Spatio-Temporal Video Object Segmentation via Scale-Adaptive 3D Structure Tensor
    Hai-Yun Wang
    Kai-Kuang Ma
    [J]. EURASIP Journal on Advances in Signal Processing, 2004
  • [42] 3D C-string: a new spatio-temporal knowledge representation for video database systems
    Lee, AJT
    Chiu, HP
    Yu, P
    [J]. PATTERN RECOGNITION, 2002, 35 (11) : 2521 - 2537
  • [43] Video algebra for spatio-temporal reasoning of iconic videos represented in 3D C-string
    Lee, Anthony J. T.
    Yu, Ping
    Chiu, Han-Pang
    Lin, Hsiu-Hui
    [J]. JOURNAL OF INFORMATION SCIENCE AND ENGINEERING, 2007, 23 (01) : 1 - 19
  • [44] Spatio-temporal video object segmentation via scale-adaptive 3D structure tensor
    Wang, HY
    Ma, KK
    [J]. EURASIP JOURNAL ON APPLIED SIGNAL PROCESSING, 2004, 2004 (06) : 798 - 813
  • [45] DUST: Dual Union of Spatio-Temporal Subspaces for Monocular Multiple Object 3D Reconstruction
    Agudo, Antonio
    Moreno-Noguer, Francesc
    [J]. 30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017), 2017, : 1513 - 1521
  • [46] Spatio-temporal Sampling for Video
    Shankar, Mohan
    Pitsiauis, Nikos P.
    Brady, David
    [J]. IMAGE RECONSTRUCTION FROM INCOMPLETE DATA V, 2008, 7076
  • [47] Spatio-temporal geometry fusion for multiple hybrid cameras using moving least squares surfaces
    Kuster, Claudia
    Bazin, Jean-Charles
    Oztireli, Cengiz
    Deng, Teng
    Martin, Tobias
    Popa, Tiberiu
    Gross, Markus
    [J]. COMPUTER GRAPHICS FORUM, 2014, 33 (02) : 1 - 10
  • [48] Joint Spatio-temporal Depth Features Fusion Framework for 3D Structure Estimation in Urban Environment
    Nawaf, Mohamad Motasem
    Tremeau, Alain
    [J]. COMPUTER VISION - ECCV 2012, PT III, 2012, 7585 : 526 - 535
  • [49] 3D-CSTM: A 3D continuous spatio-temporal mapping method
    Cong, Yangzi
    Chen, Chi
    Yang, Bisheng
    Li, Jianping
    Wu, Weitong
    Li, Yuhao
    Yang, Yandi
    [J]. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2022, 186 : 232 - 245
  • [50] Using multiple spatio-temporal features to estimate video quality
    Freitas, Pedro Garcia
    Akamine, Welington Y. L.
    Farias, Mylene C. Q.
    [J]. SIGNAL PROCESSING-IMAGE COMMUNICATION, 2018, 64 : 1 - 10