搜索资源列表
pedsim-0-99
- 行人模拟，开源的程序，对行人模拟的可以联系我，mjliao@163.com-pedestrian simulation, revenue procedures, simulated pedestrians can contact me, mjliao@163.com
20081004
- GMM 混合高斯自适应背景维护 可以用来做行人检测 等
基于团块的运动目标检测
- 改程序用于运动目标检测，可以快速准确的检测出运动目标，如行人，车辆等
peopleandbycecledetect
- 这是一篇基于BP神经网络的行人和自行车交通识别方法的文章~-people and bicycle detect
bpsuanfa
- 这是一篇基于BP神经网络的行人和自行车交通识别方法的文章~-bp shenjingwangluo
HOG
- 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
Moveman
- 用matlab编写的视频目标跟踪程序，可以跟踪路上的行人-Prepared using matlab video target tracking program, you can track the path of pedestrian
FaceRecognitionByMatLab
- 結合webcam 進行人臉辨識並有GUI方便可正確執行-Combined with webcam for face recognition and can facilitate the correct implementation of GUI
TLD
- 使用TLD进行行人检测，速度很快，效果很好
HOG-LBP-detection
- matlab 实现的hog和lbp 结合的行人检测-matlab hog-lbp detection
learcode
- 行人检测源程序，居于svm技术。和梯度直方图提取-Pedestrian Detection source, living in SVM technology. And gradient histogram extraction
xiayudelu
- 程序描绘了下雨的时候路上行人撑伞离去的景象-Program describes the umbrella when it rains left the scene of the pedestrian way
pedestrians128x64.tar
- MIT行人检测数据库，包含了924副行人图像。是计算机视觉领域的重要数据库。-MIT pedestrian detection database, contains 924 pedestrian images. Is an important field of computer vision database.
PedestrianDetectionHoG
- HOG特征行人检测 SVM支持向量机 分类-HOG feature pedestrian detection SVM support vector machine classification
零速校正原版
- 利用零速检测检测零速时刻然后进行零速校正进行行人导航(Zero speed detection is used to detect the zero speed moment, and then zero velocity correction is used for pedestrian guidance)
matlab代码
- 基于matlab的行人检测代码 排名第2的目标检测算法：基于加州理工学院2009年行人检测的文章：Integral Channel Features（积分通道特征）(Pedestrian detection code based on MATLAB)
HOG 行人检测代码
- 本文针对运动目标的检测和跟踪这一研究课题，深入研究了两种非常重要的检测和跟踪技术-光流技术和帧差法的检测技术，在运动目标检测和跟踪中的应用中，对光流法和帧差法的优缺点进行了实验分析，文中所描述的这两种检测和跟踪技术和方法都通过仿真实验进行了验证。(Detection and tracking of moving targets, the author of this paper the research topic, further study of the two very important
Adaboost
- 用Adaboost实现行人检测中的漏检率，与boosting进行比对。(Using Adaboost to achieve missed detection rate in pedestrian detection, compared with boosting.)
DPM
- 行人检测的很好，现在很多数据库都用DPM做这个检测(Pedestrian detection is very good. Now many databases use DPM to do this detection.)
Dropout
- Learning Deep Feature Representations with Domain Guided Dropout for Person Re-identification 2016年CVPR的一篇论文 行人再识别方法(Learning Deep Feature Representations with Domain Guided Dropout for Person Re-identification A CVPR Paper 2016 Pedestrian Reidenti