Data captured by a Tele-Immersion (TI) system can be very large. Compression is usually needed to ensure real-time data transmission.
Our compression method takes advantage of prior knowledge of objects, e.g. human figures, in the TI environments and represents their motions using just a few parameters. The main steps of our approach include: motion estimation and residual computation as shown in the figure above.
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.