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The paper is to propose a framework to qualitatively and quantitatively evaluate five of state-of-the-art over-segment approaches. Moreover upon over-segments evaluation, an efficient approach is developed for dense stereo matching through robust higher-order MRFs and graph cut based optimization, which combines the conventional data and smoothness terms with the robust higher-order potential term...
Current telepresence systems, while being a great step forward in videoconferencing, still have important points to improve in what eye-contact, gaze and gesture awareness concerns. Many-to-many communications are going to greatly benefit from mature auto-stereoscopic 3D technology; allowing people to engage more natural remote meetings, with proper eye-contact and better spatiality feeling. For this...
Segmentation-based approach has shown significant success in stereo matching. By assuming pixels within one image segment belong to the same 3D surface, robust depth estimation can be achieved by taking the whole segment into consideration. However, segmentation has been mostly used for stereo matching at integer disparities rather than subpixel disparities. One major reason is that small segments...
We propose a novel method to synthesize intermediate views from two stereo images and disparity maps that is robust to errors in disparity maps. The proposed method computes a placement matrix from each disparity map that can be used to correct errors when warping pixels from reference view to virtual view. The second contribution is a new hole filling method that uses depth, edge, and segmentation...
The estimation of road profiles from low texture stereo images is a problematic task because the disparity images computed from such class of images have a large number of noisy disparities. This paper presents a new method that is based on edge maps to guide the cost aggregation process in the stereo matching problem. Using the proposed aggregation method, the disparity images are smooth at low texture...
We present a robust camera pose estimation approach for stereo images captured in untextured environments. Unlike most of existing registration algorithms which are point-based and make use of intensities of pixels in the neighborhood, our approach imports line segments in registration process. With line segments as primitives, the proposed algorithm is capable to handle untextured images such as...
In this paper, we propose an efficient local stereo algorithm for accurate disparity estimation. First, we attain initial disparity estimates by iterating a cross-based cost aggregation process. Then, we propose a robust voting scheme to refine the initial estimates based on a piecewise smoothness prior, improving the quality in occluded regions and low-textured regions effectively. The refinement...
Most algorithms in stereo vision work on rectified images and therefore find the point correspondences row by row. So especially for standard block-matching algorithms periodic patterns are a problem in determining corresponding features reliably.This contribution describes a segment-based approach that allows the detection and removal of single outliers in an arbitrary dense disparity map and so...
This paper presents a new stereo matching algorithm based on inter-regional cooperative optimization. The proposed algorithm uses regions as matching primitives and defines the corresponding region energy functional for matching by utilizing the color statistics of regions and the constraints on smoothness and occlusion between adjacent regions. In order to obtain a more reasonable disparity map,...
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