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Stereoscopic video generation using motion vector based depth with k-means color segmentation

机译:基于运动矢量的基于运动矢量的立体视频生成,K均值彩色分割

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Now a day's 3d video applications becoming more and more popular in our daily life. Although more and more 3d applications are made but they are not still enough quality and comfort viewing. There is rising demand for new algorithms to generate stereoscopic video. Stereoscopic video is an illusion effect of the human eye due to the difference in the perception of the left and right eye images which leads to stereo effect. The purpose of this work is to generate low quality of stereoscopic video from the monoscopic video. Input source video to estimate the depth map based on motion vectors (MV), K-means color quantization and segmentation map to get a stereo video which is also known as 3D video. Later fusion with depth and segmentation map is a step to get the final depth map. Filtering is applied to final depth map to avoid the clipping effect in the next step. Finally to synthesize the left-view and the right-view video using the estimated depth map, we compute the parallax value for each pixel in an video from the estimated depth map.
机译:现在,一天的3D视频应用在我们的日常生活中变得越来越受欢迎。虽然制造了越来越多的3D应用,但它们并不足够的质量和舒适的观察。对新算法的需求不断增加,以产生立体视频。立体视频是人眼的幻觉效应由于左眼图像的感知差异导致立体声效应。这项工作的目的是产生从单声道视频的低质量立体视频。输入源视频基于运动向量(MV),K-Means颜色量化和分段图以获得STEREO视频,估计基于运动矢量(MV),k-means颜色量化和分段图也称为3D视频。随后与深度和分割图的融合是获得最终深度图的步骤。过滤应用于最终深度图以避免在下一步中的剪切效果。最后使用估计的深度图综合左视图和右视图视频,我们从估计的深度图计算视频中的每个像素的视差值。

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