Tele-immersive system can improve the productivity and aid communication by allowing distributed parties to exchange information via a shared immersive experience. The TEEVE research project at the University of Illinois (UIUC) and the University of California at Berkeley (UC Berkeley) seeks to promote the application of tele-immersive environments by a holistic integration of existing components that capture, transmit, and render three-dimensional (3D) scenes in real time to convey the sense of an immersive space. However, the transmission of 3D videos poses a great challenge. First, it is bandwidth-intensive as multiple large volume 3D video streams have to be transmitted. Second, the video stream contains not only color but also depth information, which requires different treatment. While color information may be compressed in a lossy manner, the depth information should be compressed losslessly. Therefore, a 3D real-time compression algorithm must be deployed to accommodate both the bandwidth requirement and the variety of data.
In this paper, we present and evaluate two compression schemes for compressing 3D video streams containing color and depth information. For the first scheme, we use color reduction followed by background removal to compress the color information, which is then compressed along with the depth information using zlib. For the second scheme, we use motion JPEG to compress the color information and run length (RLE) coding followed by Huffman coding to compress the depth information. The experimental results of 3D videos captured from real tele-immersive environment show that: (1) the compressed data preserves enough information to communicate the 3D images effectively (minimum PSNR >40) and (2) even without inter-frame motion estimation, very high compression ratios (average >15) are achievable at speeds sufficient to allow real-time communication (average 13 ms for each video frame)
