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Description: 10多篇ICCV 2009有关动作识别的 oral paper，很值得研究-More than 10 articles ICCV 2009 relevant actions identified oral paper, it is worth studying
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Author: 丁行 |
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Description: 去雾代码,非常有效，有必要仔细读一下 17/11/2009
Author: J.-P. Tarel
LCPC-INRETS copyright
completed and corrected in 18/08/2010 and in 29/09/2010
This algorithm is described in details in
"Fast Visibility Restoration from a Single Color or Gray Level Image",
by J.-P. Tarel and N. Hautiere,
in proceedings of IEEE International Conference on Computer Vision (ICCV 09),
Kyoto, Japan, p. 2201-2208, September 29- October 2, 2009.
http://perso.lcpc.fr/tarel.jean-philippe/publis/iccv09.html
-frog remove
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Size: 16545792 |
Author: zhaoxch |
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Description: ORB是是ORiented Brief的简称。在ORB的方案中，是采用了FAST作为特征点检测算子-Ethan Rublee and Vincent Rabaud and Kurt Konolige and Gary Bradski, ORB: an efcient alternative to SIFT or SURF, ICCV 2011
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Size: 904192 |
Author: moyan |
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Description: Lei Zhang, Meng Yang, and Xiangchu Feng,
Sparse Representation or Collaborative Representation: Which Helps Face Recognition? in ICCV 2011 源代码-Lei Zhang, Meng Yang, and Xiangchu Feng,
Sparse Representation or Collaborative Representation: Which Helps Face Recognition? in ICCV 2011
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Size: 9811968 |
Author: pan yunru |
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Description: EDLines是一种快速直线检测算子，2012年在ICCV上提出，也是目前处理直线检测最快的算法之一，该算法包含三个步骤：（1）边缘提取：利用Edge Drawing (ED)算法[28,29]从灰度图像中提取边缘片段；（2）线段检测：利用最小二乘法提取直线段；（3）线段确认：遵循Helmholtz定律，从已提取的直线段中摒弃虚假线段。EDLines算法的优越性得益于Edge Drawing (ED)算法能够从灰度图像中准确、快速、稳定地提取出光滑、完整的边缘片段。Edge Drawing (ED)算法包含以下步骤：
（1）采用size=5*5,σ=1的高斯核对灰度图像进行平滑滤波，去除噪声；
（2）采用一种常用的梯度算子，如Prewitt、Sobel或Scharr等计算平滑后图像中每个像素点的梯度幅度和梯度方向；
（3）将梯度图中邻域内幅度最大的像素点标记为锚点，这些锚点成为图像边缘点(edge elements)的概率很大；
（4）将相邻的锚点连接成边缘线。从一个锚点起始，ED利用相邻像素的梯度幅度和方向在梯度为最大值的锚点之间游走。
-Edge Drawing (ED) is our recently-proposed, novel, fast edge detection algorithm. What makes ED stand out
the existing edge detectors, e.g., Canny, is the following: While the other edge detectors give out a binary
edge image as output, where the etected edge pixels are usually independent, discontinuous entities ED produces a
set of edge segments, which are clean, contiguous, i.e., connected, chains of edge pixels. Thus, while the output of
the other edge detectors requires urther processing to generate potential object boundaries, which may not even be
possible or result in inaccuracies ED not only produces perfectly connected object boundaries by default, but it also achieves this in blazing speed compared to other edge detector.
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Size: 5152768 |
Author: zhanglei |
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