Title :
Skeleton-Based Compression of 3-D Tele-Immersion Data
Author :
Lien, Jyh-Ming ; Bajcsy, Ruzena
Author_Institution :
George Mason University, Fairfax, VA, 20120, jmlien@gmu.edu
Abstract :
Due to technology advances, reconstructing three-dimensional representations of physical environments in real time using cheap and non-professional cameras and PCs becomes possible. These advances will make 3-D tele-immersive environments available for everyone in the near future. However, the amount of data captured, by a Tele-Immersion (TI) system can be very large. Compression is needed to ensure real-time transmission of the data. Due to this real-time requirement, compressing TI data can be a challenging task and no current techniques can effectively address this issue. In this paper, we propose a skeleton-based compression. The main idea of this approach is to take advantage of prior knowledge of objects, e.g., human figures, in the physical environments and to represent their motions using just a few parameters. The proposed compression method provides tunable and high compression ratios (from 50:1 to 5000:1) with reasonable reconstruction quality, Moreover, the proposed method can estimate motions from the noisy data captured by our TI system in real time.
Keywords :
Bandwidth; Cameras; Humans; Image reconstruction; Motion estimation; Personal communication networks; Real time systems; Signal to noise ratio; Space technology; Working environment noise;
Conference_Titel :
Distributed Smart Cameras, 2007. ICDSC '07. First ACM/IEEE International Conference on
Conference_Location :
Vienna, Austria
Print_ISBN :
978-1-4244-1354-6
Electronic_ISBN :
978-1-4244-1354-6
DOI :
10.1109/ICDSC.2007.4357543