Description:
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 Kolmogorov and Ramin Zabih
\"Computing Visual Correspondence with Occlusions using Graph Cuts\"
In: International Conference on Computer Vision, July 2001.
and
Yuri Boykov, Olga Veksler and Ramin Zabih
\"Markov Random Fields with Efficient Approximations\"
In: IEEE Computer Vision and Pattern Recognition Conference, June 1998. -stereo algorith ms described in the following papers : Vladimir Kolmogorov and Ramin Zabih "Multi-Ca mera scene Reconstruction via Graph Cuts "In : European Conference on Computer Vision, May 2002. Vladimir Kolmogorov and Ramin Zabih " Correspondence with Visual Computing Occlusi ons using Graph Cuts "In : International Conference on Computer Vision, July 2001. and Yuri Boykov, Olga Veksler and Ramin Zabih "Markov Random Fie Efficient Bayesian lds with "In : IEEE Computer Vision and Pattern Recognition C onference, democratic governance. Platform: |
Size: 915541 |
Author:Chen |
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Description: 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 Hough transforms
* Image-based lighting for illuminating scenes and objects with real-world light images
* Content-based image retrieval, covering queries, representation, indexing, search, learning, and more
* Face detection, alignment, and recognition--with new solutions for key challenges
* Perceptual interfaces for integrating vision, speech, and haptic modalities
* Development with the Open Source Computer Vision Library (OpenCV)
* The new SAI framework and patterns for architecting computer vision applications Platform: |
Size: 12192309 |
Author:kankan |
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Description: 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 Reconstruction via Graph Cuts"
In: European Conference on Computer Vision, May 2002.
Vladimir Kolmogorov and Ramin Zabih
"Computing Visual Correspondence with Occlusions using Graph Cuts"
In: International Conference on Computer Vision, July 2001.
and
Yuri Boykov, Olga Veksler and Ramin Zabih
"Markov Random Fields with Efficient Approximations"
In: IEEE Computer Vision and Pattern Recognition Conference, June 1998.
Platform: |
Size: 1319269 |
Author:newship@126.com |
Hits:
Description:
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 Kolmogorov and Ramin Zabih
"Computing Visual Correspondence with Occlusions using Graph Cuts"
In: International Conference on Computer Vision, July 2001.
and
Yuri Boykov, Olga Veksler and Ramin Zabih
"Markov Random Fields with Efficient Approximations"
In: IEEE Computer Vision and Pattern Recognition Conference, June 1998. -stereo algorith ms described in the following papers : Vladimir Kolmogorov and Ramin Zabih "Multi-Ca mera scene Reconstruction via Graph Cuts "In : European Conference on Computer Vision, May 2002. Vladimir Kolmogorov and Ramin Zabih " Correspondence with Visual Computing Occlusi ons using Graph Cuts "In : International Conference on Computer Vision, July 2001. and Yuri Boykov, Olga Veksler and Ramin Zabih "Markov Random Fie Efficient Bayesian lds with "In : IEEE Computer Vision and Pattern Recognition C onference, democratic governance. Platform: |
Size: 1393664 |
Author:Chen |
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Description: 人脸识别论文：《采用Adaboost算法进行面部表情识别》《动态权值预划分实值Adaboost人脸检测算法》《改进的AdaBoost分类器在视频中的体育场景检测》-Face recognition thesis: the use of Adaboost algorithm to identify facial expressions, dynamic weight pre-classified real Adaboost face detection algorithm, Improved AdaBoost classifier of sports in the video scene detection Platform: |
Size: 520192 |
Author:王云 |
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Description: 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 Platform: |
Size: 1937408 |
Author:chunxiao |
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Description: 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 to a variety of purposes, such as perimeter security and intrusion detection, tripwire detection, detection of illegal parking of vehicles. Platform: |
Size: 40960 |
Author:zhangjc |
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Description: 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 intertwined since their early
days, some four decades ago with the emergence of fast digital computing. All computer vision
techniques could be regarded as a form of pattern recognition, in the broadest sense of
the term. Platform: |
Size: 12429312 |
Author:Vitali |
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Description: 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, it is really good, let' s see it Platform: |
Size: 1032192 |
Author:changfeng |
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Description: 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 recognition Neural Network. The
algorithm was tested with 2820 natural scene gray level vehicle
images of different backgrounds and ambient illumination.
The camera focused on the plate, while the angle of view and
the distance from the vehicle varied according to the
experimental setup. The license plates properly segmented
were 2719 over 2820 input images (96.4 ). The Optical
Character Recognition (OCR) system is a two layer
Probabilistic Neural Network with topology 108-180-36, whose
performance reached 97.4 . The PNN was trained to identify
multi-font alphanumeric characters from car license plates
based on data obtained from algorithmic image processing. Platform: |
Size: 831488 |
Author:keithe |
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Description: 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 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. Platform: |
Size: 31778816 |
Author:qinlei |
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Description: 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 a database of patterns of faces.
"Patterns? Yes, the cameras covered thousands of facial structures and the relative position of different elements that make up the face:
The structure of the eyes and nose.
The distance between the eyes and nose.
The size and shape of the face.
The color temperature of the skin.
Platform: |
Size: 863232 |
Author:lucdaro |
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Description: 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 identification. Platform: |
Size: 1297408 |
Author:江志浩 |
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Description: 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 process of picking the fruit apple picking robot detection and recognition has been studied in machine vision technology presents a new round shape detection algorithm, effectively achieve the Apple feature extraction. Platform: |
Size: 2507776 |
Author:tanzheng |
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Description: 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 Platform: |
Size: 10705920 |
Author:冯阳 |
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Description: deep learning code it helpful the begainer in deep learning-deep learning code it helpful the begainer in deep learning Platform: |
Size: 758784 |
Author:qiao |
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Description: 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) Platform: |
Size: 17403904 |
Author:qinqin |
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Description: 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) Platform: |
Size: 185344 |
Author:xcl小马哥
|
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Description: 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。以此类推就可以依次改FEATURE 和CLASSIFIER 形成第二种情况：bags of sifts描述和最近邻分类器和第三种情况：bags of sifts描述和线性svm分类器进行场景分类识别。(This document is an image scene recognition and classification of procedures have been run successfully.) Platform: |
Size: 18185216 |
Author:wujie123 |
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Search - scene recognition