Description: 这是最简洁，注释得最好的HOG(Histogram Oriented Gradient)算法的matlab实现。可用于行人识别和物体跟踪。-This code is well commented, which enables the adjusting of the HOG parameters. 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. Platform: |
Size: 2048 |
Author:袁宇 |
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Description: IT S A MATLAB CODE FOR HISTOGRAM OF GRADIENT ORIENTED.-IT S A MATLAB CODE FOR HISTOGRAM OF GRADIENT ORIENTED. Platform: |
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Author:na |
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Description: Histogram of Oriented Gradients (HOG) are feature descriptors used in computer vision and image processing for the purpose of object detection. The technique counts occurrences of gradient orientation in localized portions of an image. This method is similar to that of edge orientation histograms, scale-invariant feature transform descriptors, and shape contexts, but differs in that it is computed on a dense grid of uniformly spaced cells and uses overlapping local contrast normalization for improved accuracy. Platform: |
Size: 1024 |
Author:Mohammad |
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Description: 本文提出了一种复杂条件下基于子空间梯度方向直方图跟踪的方法,通过大量样本的离线训练构建目标的投影子空间,并用梯度方向直方图在子空间的投影作为新的目标描述特征. 为了满足实时性的要求,采用积分直方图方法
提高粒子特征的计算速度 然后结合粒子滤波方法在子空间中计算粒子与训练样本集之间的相似度,进而估计目标的运动参数.-A subspace t racking method is proposed to t rack target s under complex environment s. First ,
target is represented by subspace histogram of oriented gradient descriptor , which is comp uted by
projecting histograms of oriented gradient descriptor to a subspace , t hat is built f rom a large set of
t raining samples before t racking. Then an integral histogram met hod is incorporated to reduce the
comp utational complexity. By t hese , t he t racking problem is formulated as a state inference problem
under t he particle filter f ramework of target motion parameter estimation. Platform: |
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Author:wenping |
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Description: Histogram of Oriented Gradient toolbox, can be used for object detection and object recognition. This code is not for commercial purpose. Platform: |
Size: 27648 |
Author:txrubish |
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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. Platform: |
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Author:王萌 |
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Description: HOG即histogram of oriented gradient, 是用于目标检测的特征描述子，该技术将图像局部出现的方向梯度次数进行计数，该方法和边缘方向直方图、scale-invariant feature transform类似，不同的是hog的计算基于一致空间的密度矩阵来提高准确率。Navneet Dalal and Bill Triggs首先在05年的CVPR中提出HOG，用于静态图像or视频的行人检测。-HOG i.e. histogram of oriented gradient, is used to describe the characteristics of the sub-object detection, the driving frequency and the technique of local image gradient appeared was counted, and the edge direction histogram method, scale-invariant feature transform is similar, except that the hog consistent with the calculation based on the density matrix of space to improve accuracy. Navneet Dalal and Bill Triggs HOG first proposed in 2005 in the CVPR for still images or video pedestrian detection. Platform: |
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Author:王飞 |
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Description: HOG（Histogram of Oriented Gradient）方向梯度直方图，主要用来提取图像特征，最常用的是结合svm进行行人检测。-HOG (Histogram of Oriented Gradient) direction of the gradient histogram is mainly used to extract image features, the most commonly used is a combination of svm detect pedestrians. Platform: |
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Author:flyingeye10 |
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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.) Platform: |
Size: 49152 |
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.) Platform: |
Size: 162816 |
Author:赵阿敏 |
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