EStereo is a computer vision C++ library for real-time disparity estimation. It computes dense stereo matching from 2 or 3 images as well as 3D scene reconstruction. The library also comes with a GUI-based application
Future processors will likely have large on-chip caches with a possibility of dedicating an entire die for on-chip storage in a 3D stacked model. With the ever growing disparity between transistor and wire delay, the properties of such large caches
Cooperative Fusion of Stereo and Motion This paper presents a new matching algorithm based on cooperative fusion of stereo and motion cues. In this algorithm, stereo disparity and image flow values are recovered from two successive pairs of stereo i
—Estimating 3D information from an image sequence has long been a challenging problem, especially for dynamic scenes. In this paper, a novel semi-automatic 2D-to-3D conversion method is presented to estimate the disparity maps for regular 2D video s
UV-视差做目标检测的论文 this paper presents an on-road objects detection approach improved by our previous work in defining the traffic area and new strategy in obstacle extraction from U-disparity
Disparity estimation for binocular stereo images finds a wide range of applications. Traditional algorithms may fail on featureless regions, which could be handled by high-level clues such as semantic segments. In this paper, we suggest that appropri
Regional Economic Disparity, Financial Disparity, and National Economic Growth: Evidence from China，彭建刚， Bong-Soo Lee，Since China began its economic reform and opening up, the Chinese economy has enjoyed steady economic growth. However, the disparit
Color inconsistency is an urgent problem to be solved in free viewpoint television. In this letter, a new color correction method is proposed by using disparity vector information. At first, we separate foreground and background from the scene with a
The stereo vision could obtain the 3-D coordinate of the detected object by computing the disparity of the corresponding image points. However, on account of the time complexity and the low robustness of the image matching algorithm, it is seldom use
