Reliable stereoscopic video streaming considering important objects of the scene
In this paper, we introduce a new reliable method of stereoscopic Video Streaming based on multiple description coding strategy. The proposed multiple description coding generates 3D video descriptions considering interesting objects contained in its scene. To be able to find interesting objects in the scene, we use two metrics from the second order statistics of the depth map image in a block-wise manner. Having detected the objects, the proposed multiple description coding algorithm generates the 3D video descriptions for the color video using a non-identical decimation method with respect to the identified objects. The objective test results verify the fact that the proposed method provides an improved performance than that provided by the polyphase subsampling multiple description coding and our previous work using pixel variation.
|Keywords||3D/Multiview video, Coefficient of variation, Color image, Depth map, Error prone environment, Multiple description coding, Pixel variation, Region of interest, Stereoscopic video|
|Conference||13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2018|
Rahimi, E. (Ehsan), & Joslin, C. (2018). Reliable stereoscopic video streaming considering important objects of the scene. In VISIGRAPP 2018 - Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (pp. 135–142).