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{Dynamic Probabilistic Volumetric Models}


Conference Paper


This paper presents a probabilistic volumetric framework for image based modeling of general dynamic 3-d scenes. The framework is targeted towards high quality modeling of complex scenes evolving over thousands of frames. Extensive storage and computational resources are required in processing large scale space-time (4-d) data. Existing methods typically store separate 3-d models at each time step and do not address such limitations. A novel 4-d representation is proposed that adaptively subdivides in space and time to explain the appearance of 3-d dynamic surfaces. This representation is shown to achieve compression of 4-d data and provide efficient spatio-temporal processing. The advances of the proposed framework is demonstrated on standard datasets using free-viewpoint video and 3-d tracking applications.

Author(s): Ulusoy, Ali Osman and Biris, Octavian and Mundy, Joseph L.
Book Title: ICCV
Pages: 505-512
Year: 2013

Department(s): Perceiving Systems
Bibtex Type: Conference Paper (inproceedings)
Paper Type: Conference

DOI: 10.1109/ICCV.2013.68

Links: video
Attachments: pdf


  title = {{Dynamic Probabilistic Volumetric Models}},
  author = {Ulusoy, Ali Osman and Biris, Octavian and Mundy, Joseph L.},
  booktitle = {ICCV},
  pages = {505-512},
  year = {2013}