Remote visualization for 3D dynamic scene based on image space

In remote visualization for complex 3D dynamic scene, compression and transmission for vertex trajectory needs computing huge vertex and has very slow computational speed. In order to solve these problems, we present a remote visualization method for 3D dynamic scene based on image space, which replaces vertex trajectory with sample trajectory to reduce the vertex number in computation and presents a parallel compression method to realize rapid and effect compression for dynamic datasets. First, adaptive sampling algorithm in space and time (time after space) using graphics pipeline and the construction of samples connective information is presented to obtain many animated depth images. Then, the trajectory of samples is compressed in parallel in each animated depth image, which reduces compression time effectively. Finally, compressed dynamic datasets are transferred to the client and 3D dynamic scene over some time is reconstructed. Reconstructed 3D dynamic scene during some time supplies the client with observation in arbitrary angles and has little decline in rendering quality. Exprement results also show that the algorithms realize rapid compression and reduce the number of dynamic datasets greatly, which reduce network latency limitation effectively.