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Abstract

In the paper, two preprocessing methods for virtual view synthesis are presented. In the first approach, both horizontal and vertical resolutions of the real views and the corresponding depth maps are doubled in order to perform view synthesis on images with densely arranged points. In the second method, real views are filtered in order to eliminate blurred or improperly shifted edges of the objects. Both methods are performed prior to synthesis, thus they may be applied to different Depth-Image-Based Rendering algorithms. In the paper, for both proposed methods, the achieved quality gains are presented.
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Abstract

In this paper, a modification of the graph-based depth estimation is presented. The purpose of proposed modification is to increase the quality of estimated depth maps, reduce the time of the estimation, and increase the temporal consistency of depth maps. The modification is based on the image segmentation using superpixels, therefore in the first step of the proposed modification a segmentation of previous frames is used in the currently processed frame in order to reduce the overall time of the depth estimation. In the next step, a depth map from the previous frame is used in the depth map optimization as the initial values of a depth map estimated for the current frame. It results in the better representation of silhouettes of objects in depth maps and in the reduced computational complexity of the depth estimation process. In order to evaluate the performance of the proposed modification the authors performed the experiment for a set of multiview test sequences that varied in their content and an arrangement of cameras. The results of the experiments confirmed the increase of the depth maps quality — the quality of depth maps calculated with the proposed modification is higher than for the unmodified depth estimation method, apart from the number of the performed optimization cycles. Therefore, use of the proposed modification allows to estimate a depth of the better quality with almost 40% reduction of the estimation time. Moreover, the temporal consistency, measured through the reduction of the bitrate of encoded virtual views, was also considerably increased.
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