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Description: extract dense sift for each image patch, because no salient keypoint detection and rotation normalization, it is very efficient.
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Author: 郭恺 |
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Description: Hog try I try to implement hog descriptor
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Author: RidvanDongelci |
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Description: 本文运用尺度空间理论检测人体，通过集成
面向梯度与histogramof尺度空间理论
-Human detection is the task of finding presence and position
of human beings in images. In this paper, we apply
scale space theory to detecting human in still images. By integrating
scale space theory with histogramof oriented gradients
(HOG), we designed a new feature descriptor called
scale space histogram of oriented gradients (SS-HOG). SSHOG
focus on the multiple scale property of describe an
object. Using HOGs at multiple scale, SS-HOG encodes
more information to discriminate human bodies from other
object types than traditional uni-scale HOGs. Experiments
on INRIA person dataset demonstrate the effectiveness of
our method.
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Author: 谷川 |
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Description: Image descriptor based on Histogram of Orientated Gradients for gray-level images. This code
was developed for the work: O. Ludwig, D. Delgado, V. Goncalves, and U. Nunes, Trainable
Classifier-Fusion Schemes: An Application To Pedestrian Detection, In: 12th International IEEE
Conference On Intelligent Transportation Systems, 2009, St. Louis, 2009. V. 1. P. 432-437. In
case of publication with this code, please cite the paper above.- Image descriptor based on Histogram of Orientated Gradients for gray-level images. This code
was developed for the work: O. Ludwig, D. Delgado, V. Goncalves, and U. Nunes, Trainable
Classifier-Fusion Schemes: An Application To Pedestrian Detection, In: 12th International IEEE
Conference On Intelligent Transportation Systems, 2009, St. Louis, 2009. V. 1. P. 432-437. In
case of publication with this code, please cite the paper above.
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Author: Arij |
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Description: HOG descriptors 是应用在计算机视觉和图像处理领域，用于目标检测的特征描述器。-HOG descriptors are used in computer vision and image processing for target detection feature descriptor.
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Author: 王战新 |
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Description: 为了准确地对监控场景中的运动目标进行语义上的分类， 提出了一种基于聚类的核主成分分析梯度方向直方图和二叉决策树支持向量机的运动目标分类算法．利用背景减法提取运动目标前景区域， 并识别出潜在候选运动目标．利
用提出的基于聚类的核主成分分析的梯度直方图描述子提取候选运动目标的特征， 以较低维数的数据有效地描述运动目标的有效特征． 将提取的运动目标特征输入二叉决策树支持向量机， 实现多类目标的准确分类． 通过在不同视频序列上的实验验证， 提出的算法对运动目标进行较好地分类， 而且在运算速度方面较传统目标分类方法有了明显的提高． 实验结果证明了算法对运动目标分类具有较好的准确性 可靠性和鲁棒性．-For the purpose of semantically classifying moving objects accurately in a surveillance scene，a moving objects classification method based on the clustered kernel principal component analysis ( CKPCA) of the histogram
of oriented gradients ( HOG) and support vector machine ( SVM) was proposed． Firstly，the moving areas in the
foreground were extracted by means of the background subtraction method，and some of them were identified as potential candidates of moving objects． Secondly，the characteristics of the moving objects were obtained by the CKPCA- HOG descriptor，which could describe the moving objects＇ effective features at a lower data dimension． Finally，the data characteristics were fed into a binary SVM decision tree，and the final multi- class classification results were obtained accurately． After verifying different video sequences，the algorithm was able to classify moving targets very well． Compared with traditional classification methods，the proposed method makes obvious improv
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Author: 高峰 |
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Description: 分成不同的class以用來計算hog descriptor-hog calculation
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Size: 3072 |
Author: 翁藝睿 |
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Description: it s HoG descriptor, the writer code has some errors, and I have correct the errors, and the code is right under C+-it s HoG descriptor, the writer code has some errors, and I have correct the errors, and the code is right under C+
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Author: fzernike |
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Description: Hog descriptor for image analysis
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Size: 545792 |
Author: Avinash |
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Description: 方向梯度直方图（Histogram of Oriented Gradient, HOG）特征是一种在计算机视觉和图像处理中用来进行物体检测的特征描述子。它通过计算和统计图像局部区域的梯度方向直方图来构成特征。Hog特征结合SVM分类器已经被广泛应用于图像识别中，尤其在行人检测中获得了极大的成功。需要提醒的是，HOG+SVM进行行人检测的方法是法国研究人员Dalal在2005的CVPR上提出的，而如今虽然有很多行人检测算法不断提出，但基本都是以HOG+SVM的思路为主。
-Histogram of Oriented Gradients (Histogram of Oriented Gradient, HOG) feature is a kind of computer vision and image processing used for object detection feature descriptor. It does this by calculating the image and statistical local areas to form a gradient orientation histogram features. Hog features combined with SVM classifier has been widely used in image recognition, especially in pedestrian detection was a great success. Need to be reminded, HOG+SVM for pedestrian detection method is to French researchers Dalal CVPR in 2005 raised, and now although there are many pedestrian detection algorithm continuously put forward, but the basic idea is to HOG+SVM based.
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Author: 王萌 |
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Description: This HOG descriptor source code.-This is HOG descriptor source code.
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Author: Gwanghyun Jo |
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Description: efficient LBP Local binary patterns (LBP) is a type of feature used for classification in computer vision. LBP is the particular case of the Texture Spectrum model proposed in 1990.[1][2] LBP was first described in 1994.[3][4] It has since been found to be a powerful feature for texture classification it has further been determined that when LBP is combined with the Histogram of oriented gradients (HOG) descriptor, it improves the detection performance considerably on some dataset-efficient LBP Local binary patterns (LBP) is a type of feature used for classification in computer vision. LBP is the particular case of the Texture Spectrum model proposed in 1990.[1][2] LBP was first described in 1994.[3][4] It has since been found to be a powerful feature for texture classification it has further been determined that when LBP is combined with the Histogram of oriented gradients (HOG) descriptor, it improves the detection performance considerably on some dataset
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Author: Rajesh Kumar |
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Description: HOG 特征描述子，用于行人检测以及目标跟踪,生成特征描述子，用于分类或后续的处理-Feature descriptor HOG
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Author: 崔宗阳 |
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Description: 下面的代码是实现HOG（附柱状图导向梯度）
描述符和目标检测，通过那伏乃尔达拉尔和比尔Triggs介绍。
所计算的特征向量是与兼容
INRIA目标检测与定位工具包
（http://pascal.inrialpes.fr/soft/olt/）-The following code is to achieve HOG (Histogram guide attached gradient) descriptor and target detection, through that V is Jorda Lal and Bill Triggs introduction. Feature vectors are calculated compatible with INRIA target detection and localization kit (http://pascal.inrialpes.fr/soft/olt/)
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Author: sdsdsdaaasd |
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Description: 方向梯度直方图（Histogram of Oriented Gradient, HOG）特征,计算机视觉和图像处理中用来进行物体检测的特征描述子的实现-Histogram of oriented gradients (Histogram of Oriented Gradient, HOG) characteristics, computer vision and image processing used for object detection feature descriptor realization
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Author: 杨洋 |
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Description: 提取图像的HOG(梯度方向直方图)特征描述符-abstract the HOG feature of images
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Author: 滕锡超 |
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Description: Example of a souce code of hog descriptor.
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Author: mstark
|
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Description: HOG 方向梯度直方图（Histogram of Oriented Gradient, HOG）特征是一种在计算机视觉和图像处理中用来进行物体检测的特征描述子(The Histogram of Oriented Gradient (HOG) feature is a feature descriptor used for object detection in computer vision and image processing.)
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Author: 就爱吃麻酱 |
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Description: 方向梯度直方图（Histogram of Oriented Gradient, HOG）特征是一种在计算机视觉和图像处理中用来进行物体检测的特征描述子。它通过计算和统计图像局部区域的梯度方向直方图来构成特征。Hog特征结合SVM分类器已经被广泛应用于图像识别中，尤其在行人检测中获得了极大的成功。需要提醒的是，HOG+SVM进行行人检测的方法是法国研究人员Dalal在2005的CVPR上提出的，而如今虽然有很多行人检测算法不断提出，但基本都是以HOG+SVM的思路为主(The Histogram of Oriented Gradient (HOG) feature is a feature descriptor for object detection in computer vision and image processing. It constructs features by computing and counting histograms of gradient directions in local regions of images. Hog features and SVM classifier have been widely used in image recognition, especially in pedestrian detection. It needs to be reminded that the method of pedestrian detection by HOG+SVM is proposed by French researcher Dalal on 2005 of CVPR, and although many pedestrian detection algorithms are constantly proposed, it is mainly based on the idea of HOG+SVM.)
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Author: 赵阿敏 |
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Description: 提取HOG特征，简洁好用，使用方便，大家可以下载使用，使用matlab实现(Extraction of HOG features)
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Author: memeda9 |
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