搜索资源列表
hog论文
- 关于图像处理的,基于HOG特征的图像人体检测技术的研究与实现。
HumanDetectTracking.rar
- 这是一个关于监控环境下实时人体检测的文章 ,希望对有需要的朋友有所帮助,human detection
Scale_Space_Histogram_of_Oriented__Gradients_for_H
- 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
Combining-face-detection-and-people-tracking-in-v
- Face detection algorithms are widely used in computer vision as they provide fast and reliable results depending on the application domain. A multi view approach is here presented to detect frontal and profile pose of people face using Histogram of
Monocular-Pedestrian-Detection-__-survey-and-expe
- The objective of this paper is to provide an overview of the current state of the art from both methodologicaland experimental perspectives. The first part of the paper consists of a survey. We cover the main components of a pedestrian detection syst
DalalThesis
- the original Thises about HOG features
HOG
- 关于梯度方向直方图的PPT PDF格式 很清楚的解释了HOG过程-PPT PDF format on the gradient direction histogram is a clear explanation of the HOG process
Improvements-of-object-detection
- 通过fisher对hog特征降维,并用于物体检测-We present a method for object detection that combines AdaBoost learning with local histogram features. On the side of learning we improve the performance by designing a weak learner for multi-valued features based on Weighte
HOG
- hog学习资料,有两篇ppt还有作者的博士论文和cvpr上的原文,对想了解此算法的人很有帮助-hog learning materials, the two ppt the author' s doctoral thesis and cvpr on the original, helpful people who want to understand this algorithm
sport-target-detection-track
- 图像梯度方向直方图(HOG)特征基础上云模型运动目标检测算法,提出HOG特征为基础的均值漂移算法 -Moving target detection algorithm of image gradient orientation histogram (HOG) features based on cloud model proposed HOG feature based on mean shift algorithm
HOG
- this code is an feature extraction called histogram of gradian(HOG)
HOG
- 基于梯度方向直方图( H OG) 特征的行人检测是目前检测精度较高的主流方法。针对基于梯度直方图特征的 行人检测存在检测精度还有待提高、向量维数大的问题, 提出使用梯度直方图统计特征加颜色频率和肤色特征描述行 人, 选取一些分类能力较强的block 作为最后的特征, 使用线性SVM 分类。在INRIA 库上的实验证明, 该方法能有效地 提高检测精度。-H istog r am o f or iented g radient( H OG) based on pedestr ian de
OBLIVION.V1.2.0416.SI.PLUS10TRN.HOG
- 十多万11是是是法规改个挂看我哈度哈市肯定能看吗-this is a good
efficientLBP
- 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
25292626
- 为了实现复杂环境下的人脸特征有效表达,提出一种改进的梯度方向直方图(HOG)人脸识别方法.首先以人脸图像网格作为采样窗口并在其上提取 HOG特征;然后将所有网格 HOG特征向量进行组合,实现整个人脸特 征表达;最后采用最近邻分类器进行识别.另外,比较了该方法与Gabor小波和局部二值模式(LBP)2种著名的人脸 局部特征表示方法的优劣.实验结果表明,在调优的 HOG参数下,在具有光照和时间环境等复杂变化的FERET人 脸库中,较少维数的 HOG特征比LBP特征有更好的表现,而且 HO
Pedestrian-Detection
- ICCV2013: 简 称UDN算法,从文中描述的检测效果来看,该方法是所有方法中最好的,并且,效果远超过其他方法。经过对论文和该算法源码的研究,该算法是与作者另外一篇 论文的方法 ,另外的论文算法做图片扫描,得到矩形框,然后用该方法对矩形框进行进一步确认,以及降低误警率和漏警率。另外的论文是:Multi-Stage Contextual Deep Learning for Pedestrian Detection 说得难听一点,这篇文章对行人检测没有多大的贡献。仅仅是用深度学习
A-new-pedestrian-detection-method
- 基于HOG和LSS特征的行人检测算法, 具有参考意义-A new pedestrian detection method based on combined HOG and LSS features