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Description: 使用sift特征对两幅图像进行匹配，标记出特征点以及匹配上的点-Use sift features on the two images matching, and mark out and matching feature points on the point
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Size: 46978048 |
Author: lilan |
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Description: we present a new method of synthesizing novel views from the vir-
tual cameras in multiview camera confi gurations for 3DTV system. We introduce a
semi N-view & N-depth framework in order to estimate disparity maps effi ciently
and correctly.
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Size: 2391040 |
Author: alex |
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Description: Optical flow or optic flow is the pattern of apparent motion of objects, surfaces, and edges in a visual scene caused by the relative motion between an observer (an eye or a camera) and the scene.[2][3] The concept of optical flow was first studied in the 1940s and ultimately published by American psychologist James J. Gibson[4] as part of his theory of affordance. Optical flow techniques such as motion detection, object segmentation, time-to-collision and focus of expansion calculations, motion compensated encoding, and stereo disparity measurement utilize this motion of the objects surfaces and edges.[5][6]-Optical flow or optic flow is the pattern of apparent motion of objects, surfaces, and edges in a visual scene caused by the relative motion between an observer (an eye or a camera) and the scene.[2][3] The concept of optical flow was first studied in the 1940s and ultimately published by American psychologist James J. Gibson[4] as part of his theory of affordance. Optical flow techniques such as motion detection, object segmentation, time-to-collision and focus of expansion calculations, motion compensated encoding, and stereo disparity measurement utilize this motion of the objects surfaces and edges.[5][6]
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Size: 1024 |
Author: velusamy |
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Description: Optical flow or optic flow is the pattern of apparent motion of objects, surfaces, and edges in a visual scene caused by the relative motion between an observer (an eye or a camera) and the scene.[2][3] The concept of optical flow was first studied in the 1940s and ultimately published by American psychologist James J. Gibson[4] as part of his theory of affordance. Optical flow techniques such as motion detection, object segmentation, time-to-collision and focus of expansion calculations, motion compensated encoding, and stereo disparity measurement utilize this motion of the objects surfaces and edges.[5][6]-Optical flow or optic flow is the pattern of apparent motion of objects, surfaces, and edges in a visual scene caused by the relative motion between an observer (an eye or a camera) and the scene.[2][3] The concept of optical flow was first studied in the 1940s and ultimately published by American psychologist James J. Gibson[4] as part of his theory of affordance. Optical flow techniques such as motion detection, object segmentation, time-to-collision and focus of expansion calculations, motion compensated encoding, and stereo disparity measurement utilize this motion of the objects surfaces and edges.[5][6]
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Size: 1024 |
Author: velusamy |
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Description: 图像匹配问题，利用彩色图像梯度与像素的SAD法得到图像左右视差图，并利用WTA法得到准确视差-Image matching, color image gradient pixel SAD obtained disparity map image around, and WTA method to get an accurate parallax
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Size: 355328 |
Author: 小石头 |
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Description: An algorithm to calculate disparity map from stereoscopic image pairs based on Cross-based adaptive window.
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Size: 500736 |
Author: Johan |
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Description: 双目立体匹配中获取图像对的视差图，可用于后续的三维重建工作。-Binocular stereo matching to get the image on the disparity map can be used for subsequent 3D reconstruction.
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Size: 235520 |
Author: 王龙 |
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Description: 对双目视觉图像对进行匹配获取视差图，为后续三维重建做基础。-Binocular vision images are matched to obtain the disparity map, as a foundation for the subsequent three-dimensional reconstruction.
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Size: 234496 |
Author: 王龙 |
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Description: 实现了立体匹配的SAD算法计算视差图，结果比较理想-Using the SAD algorithm to calculate the disparity map of stereo matching, the result is good.
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Size: 1024 |
Author: wangyujie |
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Description: matlab实现图像匹配的视差图，可以用于3D重建系统，机器视觉等领域。-Matlab image matching parallax figure, and can be used in 3 D reconstruction system, machine vision, etc
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Size: 2111488 |
Author: 开降龙 |
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Description: 数字视频处理中利用自适应窗口进行视差估计的算法实现
算法理论部分来自于教材《数字视频处理》（黎洪松主编）第七章
-Digital video processing using the adaptive window disparity estimation for the algorithm
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Size: 4096 |
Author: xurui |
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Description: 输入输出的是.PGM 格式的图。
输入左右图，生成视差图
带有良好的注释-input：.pgm images(left and right)
output: disparity map
it works quickly and accuratly
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Size: 1359872 |
Author: 尚方 |
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Description: 这个是图片和真实视差图，视差范围是30，本图精度为0.125个像素。-This picture and the true disparity map, the parallax range is 30, this figure an accuracy of 0.125 pixels.
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Size: 76800 |
Author: 尚方 |
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Description: 改写过的一个简单的daisy特征提取程序，依赖opencv2.3库，可以提取daisy特征向量，并通过特征匹配求得两幅图像的视差图-Rewritten a simple daisy feature extraction program, dependent opencv2.3 library, can be extracted daisy feature vectors, and by the feature match the disparity map of the image of the obtained two
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Size: 7907328 |
Author: 陈铭 |
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Description: 输入两幅左右视差图像，计算两幅图像的视差图 可用于合成中间任意一个角度的图像。-Enter the two right and left parallax images, computing the disparity map of the two images can be used for the synthesis intermediate image to an arbitrary angle.
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Size: 1984512 |
Author: 何彦 |
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Description: 此程序使用opencv计算相应图像对的视差并作出视差图，进而以之为基础进行图像的三维重建。-This program calculates the disparity and plots the depthimage using opencv. Therefore, reconstruct the stereo image.
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Size: 775168 |
Author: 张开桓 |
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Description: 根据深度图估算左右眼视差，程序中的数据均为估算的实际值-Are estimates of the actual values of the data in the left and right eye parallax depth map estimation program
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Size: 8192 |
Author: 流颐光年 |
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Description: in this project you can find two methods to compute the disparity image using dynamic programming for stereo images.
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Size: 6144 |
Author: mazoul82 |
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Description: 实现OpenCV、OpenGL、VS2008混合编程，输入校正后的图像对，使用立体匹配算法计算其视差图，最后用OpenGL进行三维重建-Achieve OpenCV, OpenGL, VS2008 mixed programming, enter the corrected image right, using stereo matching algorithm to calculate the disparity map, the final three-dimensional reconstruction with OpenGL
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Size: 22887424 |
Author: 金媛媛 |
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Description: 出了一种恢复高质量稠密视差图的立体视觉合作算法．该算法采用基于形态学相似性的自适应加权方
法，迭代地进行局部邻域的自适应聚合和抑制放大，实现高效率和高质量稠密视差图计算．将该算法推广到三目摄像
机立体匹配系统中，通过重建摄像机坐标系实现图像校正，并根据连续性假设和唯一性假设，建立视差空间中的支持
关系和三目摄像机之间的抑制关系．实验结果表明，三目立体合作算法能够得到精确的场景视差映射，并可以实现多
基线方向的遮挡检测．该算法特别适用于由多个廉价摄像机组成的立体视觉系统，在几乎不增加软件和硬件资源的
情况下。就可以得到高质量的稠密视差图．-Out of a dense disparity map to restore quality stereoscopic cooperative algorithms. The algorithm based on adaptive weighted morphological similarity method iteratively local neighborhood adaptive aggregation and inhibition of amplification to achieve high efficiency and high quality dense disparity map calculation. The algorithm is extended to trinocular stereo matching system, by rebuilding the camera coordinate system for image correction, and assumptions based on continuity and uniqueness of the assumptions in establishing a supportive relationship disparity space and trinocular relationship between inhibition. Experimental results show that the algorithm can cooperate trinocular stereo scene accurate parallax map and can achieve more occlusion detection base line direction. The algorithm is particularly suitable for low-cost cameras consisting of a plurality of three-dimensional vision system, almost no increase in the software and the hardware resources. You can get high-quality
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Size: 769024 |
Author: aaron |
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