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match-v3.3.src
- This software implements stereo algorithms described in the following papers: Vladimir Kolmogorov and Ramin Zabih \"Multi-Camera scene Reconstruction via Graph Cuts\" In: European Conference on Computer Vision, May 2002. Vladimir
Emerging.Topics.in.Computer.Vision
- 深入浅出介绍计算机视觉的最新动态。内容包括： * Camera calibration using 3D objects, 2D planes, 1D lines, and self-calibration * Extracting camera motion and scene structure from image sequences * Robust regression for model fitting using M-estimators, RANSAC, and
computing dense correspondence graph cuts
- computing dense correspondence # # (disparity map) between two images using graph cuts This software implements stereo algorithms described in the following papers: Vladimir Kolmogorov and Ramin Zabih "Multi-Camera scene Reco
Learning-Natural-Scene-Categories
- 本文提出了一个对自然场景类别学习和识别的一个新的方法-This paper presents a scene of natural category learning and recognition of a new approach
Recognition
- 運動識別 在摄像机监视的场景范围内，对出现的运动目标进行检测、分类及轨迹追踪，可应用于各种监控目的，如周界警戒及入侵检测、绊线检测、非法停车车辆检测等。-Movement Recognition ' scene in the scope of surveillance cameras, the emergence of the moving target detection, classification and tracking, monitoring can be applied
Scene-Reconstruction-Pose-Estimation-and-Tracking
- This volume, in the ITECH Vision Systems series of books, reports recent advances in the use of pattern recognition techniques for computer and robot vision. The sciences of pattern recognition and computational vision have been inextricably inte
MILL
- 模式识别中，多标签标记中的经典代码，主要用于场景分类，目标识别，结合svm和boost算法对自然场景进行分类，真的很不错，看看吧-Pattern Recognition, multi-tagged in the classic code, mainly used for scene classification, object recognition, combined with svm and boost the natural scene classification algorithm,
getPDF2
- 本文提出了一种新的车辆许可证盘子识别,并在此基础上提出了一种自适应图像分割方法-In this paper, a new algorithm for vehicle license plate identification is proposed, on the basis of a novel adaptive image segmentation technique (Sliding Windows) in conjunction with a character recogni
ImageSeg
- 提出了一种适用于视频监控场景的基于物理反射模型的阈值分割算法，该算法主要解决背景颜色识别受 光强非均匀分布、高光效应影响的问题．算法步骤主要包括：首先基于Phong反射模型推导出漫反射分量颜色不 变性并根据这一判定条件计算得到漫反射分量系数；其次，利用微分法则实现对模型镜面反射分量系数和镜面 反射强度指数的估计；最后，根据建立的物理反射模型实现背景阚值分割．大量实验分析结果表明，文中提出的 算法利用视频监控的物理反射模型和大量统计信息，能够更好地解决受光强非均匀分布和高光效应影响
codetsu
- 用来对图像进行分类。Source code for Towards Total Scene Understanding: Classification, Annotation and Segmentation in an Automatic Framework. Computer Vision and Pattern Recognition (CVPR) 2009，Li-Jia Li, Richard Socher and Li Fei-Fei. -Source code for Towards
sanweichangjingchonggou
- 移动机器人对其工作环境的有效辨识、感知与重构，是其自主导航与环境探索的基 础和前提条件。为实现非结构化环境的三维场景重构，本文在自主移动机器人平台上构 建了三维激光测距系统，设计和开发了三维场景重构软件 采用基于线段端点的ICP算 法准确快速的实现不同视点下的场景匹配 提出了基于核心场景的多场景重构策略，并 采用栅格划分法对重合区域进行数据精简，从而实现大范围三维场景重构。本文通过对 算法的实现和实验数据的比较分析，尝试对非结构化环境三维场景重构问题进行创新性 的探索与研
esCARAbajo
- In recent times, the camera manufacturers have included a new parameter in the analysis: facial recognition. How a camera can detect if there are faces in a scene? For simple, when analyzing the data they send the AF and AE camera contrasts them with
hand-label
- 道路场景识别，通过对样本图像处理和特征提取，再通过bp神经网络进行学习，最后通过学习后得到的权值进行样本识别。-Road scene recognition, through the sample image processing and feature extraction, and then through bp neural network learning, and finally by learning the weights obtained after the sample ide
of-Apple-detection-and-recognition
- 基于机器视觉的苹果检测与识别关键技术研究 本文以自然场景下的苹果果实为研究对象，对果实采 摘机器人采摘过程中苹果的检测与识别进行了研究，在机器视觉技术上提出一种新的圆 形检测算法，有效的实现了苹果特征提取。-Apple detection based on machine vision and identification of key technologies Taking apple fruit under natural scene for the study of the
sift
- 包含了SIFT详解，对于初学图像分类，场景识别有很大帮助-Contains a detailed SIFT, for beginners of image classification, scene recognition is of great help
deep-learning-scene-recognition
- deep learning code it helpful the begainer in deep learning-deep learning code it helpful the begainer in deep learning
changjingshibiefenlei
- 本文件是图像场景识别并进行分类的程序，已运行成功。 分别利用1 tiny image描述和最近邻分类器 2 bags of sifts描述和最近邻分类器 3bags of sifts描述和线性svm分类器进行场景分类识别的。 在主程序proj3中将FEATURE 改成tiny image，CLASSIFIER 改成nearest neighbor，注释其他FEATURE 和CLASSIFIER的选择就可以实现第一种场景分类识别：tiny image描述和最近邻分类器。以此类
image_processing3
- 图像工程作业3：基于视词袋模型的场景识别 (Scene recognition with bag of words)-Image Engineering Job 3: Scene Recognition Based visual bag of words (Scene recognition with bag of words)
SpatialPyramid算法matlab实现
- SPM基于sift特征的自相关检测，可用于图像场景识别等(SPM autocorrelation detection based on SIFT features, can be used for image scene recognition)
MRCNN-Scene-Recognition-master
- scene recognition motion