An Improved Gaussian Mixture Model Based Holefilling Algorithm Exploiting Depth Information Virtual views generation is of great significance in free viewpoint video (FVV) as it can avoid the need to transmit a large volume of video data. An important issue in generating virtual views is how to fill the holes caused by occlusion. Using the Gaussian mixture model (GMM) to generate the background reference image is a commonly used holefilling method. However, GMM usually has poor performance for sequences with reciprocal motion. In this paper, we propose an improved GMMbased method. To avoid the foreground pixels misclassified as the background pixels, we use depth information to adjust the learning rate in GMM. Foreground pixel is given a smaller learning rate than the background. Further, a refined foreground depth correlation (FDC) algorithm is proposed, which generates the background frame by tracking the change of the foreground depth in the temporal direction. In contrast to existing algorithms, we use a sliding window to obtain multiple background reference frames. These reference frames are then fused together to generate a more accurate background frame. Finally, we adaptively choose the background pixel from the GMM and FDC for hole filling. The experimental results show that subjective gain can be achieved, and significant objective gain can be observed in reciprocal motion sequences.

A Novel Algebaric Variety Based Model for High Quality FreeViewpoint View Synthesis on a Krylov Subspace This paper presents a new depthimagebased rendering algorithm for freeviewpoint 3DTV applications. The cracks, holes, ghost countors caused by visibility, disocclusion, resampling problems associated with 3D warping lead to serious rendering artifacts in synthesized virtual views. This challenging problem of hole filling is formulated as an algebraic matrix completion problem on a higher dimensional space of monomial features described by a novel variety model. The highlevel idea of this work is to exploit the linear or nonlinear structures of the data and interpolate missing values by solving algebraic varieties associated with Hankel matrices as a member of Krylov subspace. The proposed model effectively handles artifacts appear in widebaseline spatial view interpolation and arbitrary camera movements. Our model has a low runtime and results excel with stateoftheart methods in quantitative and qualitative evaluation.