A method which simply generates evaluation data for sceneflow testing is presented, in which most algorithms for sceneflow estimation require a pair of depth and colour images. We scanned the 3D geometry of a real o...
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A method which simply generates evaluation data for sceneflow testing is presented, in which most algorithms for sceneflow estimation require a pair of depth and colour images. We scanned the 3D geometry of a real object and rendered it in graphical space to acquire its depth and colour information. Next, surface deformation to generate natural motion for the sceneflow is employed. The surface deformation enabled the generation of non-rigid as well as rigid motion. Next, barycentric coefficients were exploited to compute the ground truth sceneflow. The coefficients enabled the acquired dense scene to flow accurately without dense point tracking and colour information. On the other hand, each flow vector was computed per pixel and a pixel could come from more than one point due to occlusion. We compute the flow maps dividing the geometry into the front area and the occluded area by modifying a z-buffer algorithm. Experimental results showed that the proposed method reliably provided evaluation data (a pair of depth and colour images and a sceneflow map) based on a scanned model with occlusion.
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