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Computer vision
来自开放百科 - 灰狐
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* 物体与环境建模（例如工业检查，医学图像分析和拓扑建模） | * 物体与环境建模（例如工业检查，医学图像分析和拓扑建模） | ||
* 交感互动（例如人机互动的输入设备） | * 交感互动（例如人机互动的输入设备） | ||
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==理论== | ==理论== | ||
| + | [[deep learning|Deep Learning]] is the hottest topic in Computer Vision | ||
*[http://mathworld.wolfram.com/Convolution.html Convolution] | *[http://mathworld.wolfram.com/Convolution.html Convolution] | ||
*[[Convolutional neural network|卷积神经网络]] | *[[Convolutional neural network|卷积神经网络]] | ||
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==项目== | ==项目== | ||
| + | 计算机视觉的开源深度学习：Torch vs Caffe | ||
| + | |||
| + | [[image:torch-vs-caffe.jpg]] | ||
| + | [[文件:VIAME-logo.png|right|VIAME]] | ||
| + | [[文件:cvf.jpg|right]] | ||
*[[Torch]] | *[[Torch]] | ||
*[[Caffe]] | *[[Caffe]] | ||
| + | *[[TensorFlow]] | ||
*[https://github.com/luispedro/mahotas Mahotas: Python Computer Vision Library] | *[https://github.com/luispedro/mahotas Mahotas: Python Computer Vision Library] | ||
| + | *[http://libccv.org/ ccv] - a modern computer vision library | ||
| + | *[[OpenFace]] | ||
| + | *[[OpenCV]], [http://docs.huihoo.com/opencv/3.0/da/d60/tutorial_face_main.html 人脸识别] | ||
| + | *[https://github.com/BradLarson/GPUImage2 GPUImage 2] | ||
| − | == | + | ==ImageNet== |
| − | + | [[文件:imagenet-logo.jpg|right]] | |
| − | + | *[http://image-net.org ImageNet官网] | |
| − | + | *[http://vision.stanford.edu/ Stanford Vision Lab] | |
| − | + | ||
| − | + | ==文档== | |
| + | *[http://docs.huihoo.com/infoq/qconbeijing/2016/day1/%E6%96%B0%E5%85%B4%E6%8A%80%E6%9C%AF%E5%8F%8A%E5%BA%94%E7%94%A8%E4%B8%93%E9%A2%98/5-4-%E4%BA%BA%E8%84%B8%E8%AF%86%E5%88%AB%E6%8A%80%E6%9C%AF%E5%9C%A8%E5%95%86%E4%B8%9A%E9%93%B6%E8%A1%8C%E7%9A%84%E5%BA%94%E7%94%A8%E5%8F%8A%E6%8C%91%E6%88%98-%E7%8E%8B%E6%99%B6.pdf 人脸识别技术在商业银行的应用及挑战] | ||
| + | *[http://docs.huihoo.com/deep-learning/deeplearningsummerschool/2015/Seeing-People-with-Deep-Learning.pdf Seeing People with Deep Learning] | ||
| + | *[http://docs.huihoo.com/deep-learning/deeplearningsummerschool/2015/Deep-Learning-Deep-Boltzmann-Machines.pdf Deep Learning: Deep Boltzmann Machines] | ||
| + | *[http://docs.huihoo.com/gputechconf/gtc2015/S5713-Collaborative-Feature-Learning-from-Social-Media.pdf Collaborative Feature Learning from Social Media] | ||
| + | *[http://docs.huihoo.com/gputechconf/gtc2015/S5474-CloudCV-Large-Scale-Distributed-Computer-Vision-as-a-Cloud-Service.pdf CloudCV: Large-Scale Computer Vision on the Cloud] | ||
| + | *[http://docs.huihoo.com/gputechconf/gtc2015/S5580-Application-of-GPUs-to-Classification-Problems-Using-Deep-Learning-Architectures.pdf Application of GPUs to Classification Problems Using Deep Learning Architectures] | ||
| + | *[http://docs.huihoo.com/gputechconf/gtc2015/S5577-Building-State-of-Art-Face-Processing-Pipeline-with-GPU.pdf Understand Face with GPU and beyond] | ||
| + | *[http://docs.huihoo.com/gputechconf/gtc2015/S5123-Through-the-Eyes-of-a-Car-Visualizing-a-Car-Camera-System.pdf Visualizing a Car's Camera System: Computer Vision for Automotive] | ||
| + | *[http://docs.huihoo.com/gputechconf/gtc2015/S5457-Maximizing-Face-Detection-Performance-on-GPUs.pdf Maximizing Face Detection Performance] | ||
| + | *[http://docs.huihoo.com/gputechconf/gtc2015/S5182-The-Future-of-Human-Vision-Preferential-Augmentation-Using-GPUs.pdf The Future of Human Vision: Preferential Augmentation Using GPUs] | ||
==图书== | ==图书== | ||
| + | *[http://book.huihoo.com/computer-vision/Computer-Vision-Ballard-and-Brown-1982.pdf 《Ballard and Brown's Computer Vision》] | ||
*[http://book.huihoo.com/computer-vision/computer-vision-algorithms-and-applications-20100903-draft.pdf 《Computer Vision: Algorithms and Applications》近1000页] | *[http://book.huihoo.com/computer-vision/computer-vision-algorithms-and-applications-20100903-draft.pdf 《Computer Vision: Algorithms and Applications》近1000页] | ||
==视频== | ==视频== | ||
*[https://www.youtube.com/watch?v=40riCqvRoMs 李飞飞: 我们怎么教计算机理解图片？赋予计算机视觉智能] ps: 在2007年发起了[http://www.image-net.org/ ImageNet(图片网络)]计划. | *[https://www.youtube.com/watch?v=40riCqvRoMs 李飞飞: 我们怎么教计算机理解图片？赋予计算机视觉智能] ps: 在2007年发起了[http://www.image-net.org/ ImageNet(图片网络)]计划. | ||
| + | |||
| + | ==课程== | ||
| + | *[http://vision.stanford.edu/teaching.html 斯坦福计算机视觉课程] | ||
| + | *[http://www-inst.eecs.berkeley.edu/~cs280/sp15/index.html 伯克利 CS280: Computer Vision], [http://docs.huihoo.com/computer-vision/berkeley/cs280-computer-vision 幻灯片下载] | ||
| + | |||
| + | ==研究组== | ||
| + | *[https://torrvision.com/ Torr Vision Group] | ||
| + | *[https://www.robots.ox.ac.uk/~vgg/ Visual Geometry Group] | ||
| + | |||
| + | ==厂商== | ||
| + | *[https://www.azure.cn/projectoxford/vision 微软牛津计划 Computer Vision API][https://github.com/Microsoft/ProjectOxford-ClientSDK GitHub] | ||
| + | *[http://www.faceplusplus.com.cn/ Face++人脸识别] | ||
| + | *[http://deepglint.com/ 格灵深瞳]: 三维计算机视觉 + 深度学习，车辆识别和安防产品 | ||
| + | *[https://open.tuputech.com/ 图普科技]: 专注于图像识别和视觉检测 | ||
| + | *[http://sensetime.com/ 商汤科技] | ||
| + | *[http://www.sensetime.com/cn SenseTime] | ||
| + | *[http://www.hiscene.com HiScene] | ||
| + | *[[vision.ai]] | ||
| + | *[http://cloudsightapi.com/ CloudSight] | ||
| + | *[http://cloudcv.org/ CloudCV] | ||
| + | *[http://www.clarifai.com/ Clarifai] | ||
| + | *[http://vision.alchemy.ai/ Alchemy Vision], [http://www.ibm.com/smarterplanet/us/en/ibmwatson/developercloud/alchemy-vision.html IBM AlchemyVision] | ||
| + | *[https://www.imageidentify.com/ The Wolfram Language Image Identification Project] | ||
| + | *[http://www.adaptive-vision.com Machine Vision Software and Libraries - Adaptive Vision] | ||
| + | *[http://itseez.com/ Itseez - Computer Vision Consulting - Machine Learning] | ||
| + | |||
| + | ==图集== | ||
| + | <gallery> | ||
| + | image:computer-vision.png|Computer Vision | ||
| + | image:computer-vision-2.png|Compuer Vision | ||
| + | image:computer-vision-application.png|典型应用 | ||
| + | image:computer-vision-zh-cn.jpg|计算机视觉 | ||
| + | image:computer-graphics-and-computer-vision.png|计算机图形和计算机视觉 | ||
| + | image:image-processing-and-computer-vision-python-ecosystem.png|Python生态 | ||
| + | image:openface.jpg|OpenFace | ||
| + | image:metamind-imagenet-accuracy.png|ImageNet精确度 | ||
| + | image:AVCaptureStillImageOutput-CIFaceDetector.png|人脸识别 | ||
| + | image:android-face-recognition-with-deep-learning-library.png|Android人脸识别深度学习库 | ||
| + | image:Accelerated-Vision-API-Landscape-Overview.png|视觉加速API | ||
| + | </gallery> | ||
==链接== | ==链接== | ||
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*[http://vision.stanford.edu/ Stanford Computer Vision Lab] | *[http://vision.stanford.edu/ Stanford Computer Vision Lab] | ||
*[http://bvlc.eecs.berkeley.edu/ Berkeley Vision and Learning Center] | *[http://bvlc.eecs.berkeley.edu/ Berkeley Vision and Learning Center] | ||
| − | |||
| − | |||
*[http://cs.stanford.edu/people/karpathy/ Andrej Karpathy]、[https://github.com/karpathy Andrej @ GitHub] | *[http://cs.stanford.edu/people/karpathy/ Andrej Karpathy]、[https://github.com/karpathy Andrej @ GitHub] | ||
| − | |||
*[http://www.chinacloud.cn/show.aspx?id=21212&cid=17 2015深度学习回顾：ConvNet、Caffe、Torch及其他] | *[http://www.chinacloud.cn/show.aspx?id=21212&cid=17 2015深度学习回顾：ConvNet、Caffe、Torch及其他] | ||
| + | *[https://www.zhihu.com/question/20672053 计算机视觉，计算机图形学和数字图像处理，三者之间的联系和区别是什么？] | ||
| + | *[http://geek.csdn.net/news/detail/93514 基于计算机视觉的无人驾驶感知系统] | ||
| + | *[https://zhuanlan.zhihu.com/p/37736910 FlowNet到FlowNet2.0：基于卷积神经网络的光流预测算法] | ||
[[category:artificial intelligence]] | [[category:artificial intelligence]] | ||
[[category:computer vision]] | [[category:computer vision]] | ||
| + | [[category:deep learning]] | ||
| + | [[category:computer science]] | ||
2022年8月9日 (二) 10:08的最后版本
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您可以在Wikipedia上了解到此条目的英文信息 Computer vision Thanks, Wikipedia. |
Computer vision 计算机视觉
计算机视觉是一门研究如何使机器“看”的科学，更进一步的说，就是指用摄影机和计算机代替人眼对目标进行识别、跟踪和测量等机器视觉，并进一步做图像处理，用计算机处理成为更适合人眼观察或传送给仪器检测的图像。
计算机视觉系统组成部分包括：
- 过程控制（例如工业机器人和无人驾驶汽车）
- 事件监测（例如图像监测）
- 信息组织（例如图像数据库和图像序列的索引创建）
- 物体与环境建模（例如工业检查，医学图像分析和拓扑建模）
- 交感互动（例如人机互动的输入设备）
目录 |
[编辑] 理论
Deep Learning is the hottest topic in Computer Vision
[编辑] 项目
计算机视觉的开源深度学习：Torch vs Caffe
- Torch
- Caffe
- TensorFlow
- Mahotas: Python Computer Vision Library
- ccv - a modern computer vision library
- OpenFace
- OpenCV, 人脸识别
- GPUImage 2
[编辑] ImageNet
[编辑] 文档
- 人脸识别技术在商业银行的应用及挑战
- Seeing People with Deep Learning
- Deep Learning: Deep Boltzmann Machines
- Collaborative Feature Learning from Social Media
- CloudCV: Large-Scale Computer Vision on the Cloud
- Application of GPUs to Classification Problems Using Deep Learning Architectures
- Understand Face with GPU and beyond
- Visualizing a Car's Camera System: Computer Vision for Automotive
- Maximizing Face Detection Performance
- The Future of Human Vision: Preferential Augmentation Using GPUs
[编辑] 图书
[编辑] 视频
- 李飞飞: 我们怎么教计算机理解图片？赋予计算机视觉智能 ps: 在2007年发起了ImageNet(图片网络)计划.
[编辑] 课程
[编辑] 研究组
[编辑] 厂商
- 微软牛津计划 Computer Vision APIGitHub
- Face++人脸识别
- 格灵深瞳: 三维计算机视觉 + 深度学习，车辆识别和安防产品
- 图普科技: 专注于图像识别和视觉检测
- 商汤科技
- SenseTime
- HiScene
- vision.ai
- CloudSight
- CloudCV
- Clarifai
- Alchemy Vision, IBM AlchemyVision
- The Wolfram Language Image Identification Project
- Machine Vision Software and Libraries - Adaptive Vision
- Itseez - Computer Vision Consulting - Machine Learning
[编辑] 图集
Computer Vision
Compuer Vision
典型应用
计算机视觉
计算机图形和计算机视觉
Python生态
OpenFace
ImageNet精确度
人脸识别
Android人脸识别深度学习库
视觉加速API
[编辑] 链接
- The Computer Vision Foundation
- Awesome Computer Vision
- Awesome Deep Vision
- Stanford Artificial Intelligence Laboratory
- Stanford Computer Vision Lab
- Berkeley Vision and Learning Center
- Andrej Karpathy、Andrej @ GitHub
- 2015深度学习回顾：ConvNet、Caffe、Torch及其他
- 计算机视觉，计算机图形学和数字图像处理，三者之间的联系和区别是什么？
- 基于计算机视觉的无人驾驶感知系统
- FlowNet到FlowNet2.0：基于卷积神经网络的光流预测算法
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