Abstract-The complexity of the world is a factor of evaluating the visual fatigue of 3D video. Depth discontinuities are the layers of the world and can be a characteristic of the complexity of the world. We suppose a new method to extract a depth discontinuities from a disparity map. We employed DIP algorithm for extraction of the depth discontinuities with a learned threshold automatically inferred based on the average and standard deviation of the disparity, that is, depth of the stereoscopy.Index Terms-Depth discontinuities, DIP, disparity map, human visual fatigue.
Abstract-In the 3D stereoscopic images, there are very important that viewer does not feel the discomfort and fatigue. In order to detect the discomfort and fatigue in 3D stereoscopic images, the proposed method detects the excessive disparity regions using the adaptive LoG operator and binarization. The proposed method makes binary image of disparity-map using histogram-based binarization. It also performs region segmentation of the disparity-map using the adaptive LoG operator. In the segmented regions, the overlapped regions with the binarization results are detected as the excessive disparity regions.Index Terms-3D stereoscopic images, binarization, LoG operator, discomfort and fatigue, disparity-map.
Abstract-In this paper, we propose the method to extract objects with excessive disparities in 3D stereoscopic images using cost function considering the intensity and the depth information. The traditional region segmentation method such as CLRG (Centroid Linkage Region Growing) used in the general 2D images is processed only based on intensity information. 3D stereoscopic images have the additional information that is depth. In the proposed method, first the excessive disparity candidate regions are decided using the pre-defined threshold in the disparity-map. Next the extracted excessive disparity candidate regions are labeled to object regions and the other regions are labeled to background regions. The regions labeled as object are set as region that will be segmented in 3D stereoscopic left image. The proposed segmentation method considering the intensity and the depth is applied to these regions in 3D stereoscopic left image. Finally to eliminate small regions, the morphological filter is used.
In this paper, we propose the method to extract objects with excessive disparities in 3D stereoscopic images using cost function considering the intensity and the depth information. The traditional region segmentation methods use only intensity in 2D images. The 3D stereoscopic images have the additional information that is disparity. In the proposed method, first, the excessive disparity candidate regions are decided using the adaptive threshold in the disparity-map. Next, the extracted excessive disparity candidate regions are labeled to object regions and the other regions are background. The object regions are set as ROI (region of interest). The proposed segmentation method is applied in the ROI of 3D stereoscopic left image. Finally, the excessive disparity object is extracted through eliminating small regions.
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