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https://github.com/jack06215/my-awesome-list

List of learning resources, and other good stuff
https://github.com/jack06215/my-awesome-list

List: my-awesome-list

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List of learning resources, and other good stuff

Awesome Lists containing this project

README 

        
## New resources for the past 30 days

* [Automatic Upright Adjustment of Photographs With Robust Camera Calibration](http://ieeexplore.ieee.org/document/6587711/?denied)

* [Rectification of planar targets using line segments](https://link.springer.com/article/10.1007/s00138-016-0807-1)

* [Estimating the focal length of a photo from EXIF tags](http://phototour.cs.washington.edu/focal.html)

* [Dissimilarity-based Sparse Subset Selection](https://arxiv.org/pdf/1407.6810.pdf)

* [A geometric interpretation of the covariance matrix](http://www.visiondummy.com/2014/04/geometric-interpretation-covariance-matrix/)

* [the Serious Computer Vision Blog](https://computervisionblog.wordpress.com/)

* [AI Skack](http://aishack.in/)

* [情報学広場：情報処理学会](https://ipsj.ixsq.nii.ac.jp/ej/)

* [GitXiv](http://www.gitxiv.com)

* [Augmented Reality](https://prateekvjoshi.com/2012/08/02/augmented-reality/)

* [Probabilistic Randomness Of Stochasticity](https://prateekvjoshi.com/2012/07/26/probabilistic-randomness-of-stochasticity/)

* [An Interactive Guide To The Fourier Transform](https://betterexplained.com/articles/an-interactive-guide-to-the-fourier-transform/)

* [PROJECTIVE GEOMETRY](http://www.scienceofcorrespondences.com/projective-geometry.htm)

* [PRINCIPAL COMPONENT ANALYSIS IN 6 STEPS](https://coolstatsblog.com/2015/03/21/principal-component-analysis-explained/)

* [Will People Like Your Image?](http://patwie.com/#implementations)

* [VALSE -  视觉与学习青年学者研讨会](http://valser.org/)

* [VALSE Archive](http://vision.ouc.edu.cn/valse/)

* [AKAZE特徴量の紹介と他特徴量との比較](http://poly.hatenablog.com/entry/2014/01/06/063012)

* [ECCV2012で発表されたKAZE局所特徴量を試してみた](http://daily.belltail.jp/?p=1352)

* https://www.youtube.com/channel/UCEirPnFv_2QbvzrM67SnKPA/videos

* http://courses.washington.edu/am301/page2/page13/video.html

* https://engineering.purdue.edu/kak/computervision/ECE661.08/homework/HW5_LM_handout.pdf

* https://www.codeproject.com/articles/55691/neural-network-learning-by-the-levenberg-marquardt.aspx

* http://ufldl.stanford.edu/tutorial/supervised/LinearRegression/

* https://www.cs.duke.edu/courses/fall15/compsci527/notes/



## Wikipedia resources

* [List of mathematical symbols](https://en.wikipedia.org/wiki/List_of_mathematical_symbols)

* [Rotation matrix](https://en.wikipedia.org/wiki/Rotation_matrix)

* [Equation of conic](https://en.wikipedia.org/wiki/Conic_section#General_Cartesian_form)

* [Matrix representation of conics](https://en.wikipedia.org/wiki/Matrix_representation_of_conic_sections)



## Japanese

* [Jisho.org](http://jisho.org/)

### にほんごのページ

* [にほんごのページ](http://web.ydu.edu.tw/~uchiyama/)

### j-nihongo (日本語例文)

* [〜甲斐がある](http://j-nihongo.com/kaigaaru/)

* [～かねない](http://j-nihongo.com/kanenai/)

### Gagazine

* [ロボットやAIが「権利を持つに等しい存在」になった時、人間はどう考えるべきなのか？](http://gigazine.net/news/20170227-robot-rights/)

## Research Papers

* [Fast Keypoint Recognition using Random Ferns](https://pdfs.semanticscholar.org/3ea5/4da8ba5deba902e34199b63956edf68906ff.pdf)

* [Affine Covariant Feature](http://www.robots.ox.ac.uk/~vgg/research/affine/)

* [An Improved ORB Algorithm of Extracting and Matching Features](http://www.sersc.org/journals/IJSIP/vol8_no5/12.pdf)

* [Pose Tracking from Natural Features on Mobile Phones](https://data.icg.tugraz.at/~dieter/publications/Schmalstieg_142.pdf)

* [An Effective Rigidity Constraint for Improving RANSAC in Homography Estimation](https://link.springer.com/chapter/10.1007/978-3-642-17691-3_19)

* [Speeding-up homography estimation in mobile devices](http://www.dia.fi.upm.es/~pcr/publications/jrtip2015.pdf)

* [Fast Keypoint Recignition in 10 lines of code](https://pdfs.semanticscholar.org/5137/516a2604bb0828e59dc517b252d489409986.pdf)

* [Visual Object Tracking via random ferns based classification](http://www.serc.iisc.ernet.in/~venky/Papers/RandomFernsTracking_ICASSP14.pdf)

* [Local Invariant Feature Detectors: A Survey](http://www.eng.auburn.edu/~roppeth/courses/7970%202015A%20AdvMobRob%20sp15/literature/%5B2008%5D%20Local%20Invariant%20Feature%20Detectors-%20A%20Survey.pdf)

* [Binary Feature comparison](https://www.cs.unc.edu/~jheinly/publications/eccv2012-heinly.pdf)

* [Online Learning of Patch Perspective Rectification for Efficient Object Detection](http://campar.in.tum.de/personal/hinterst/index/project/CVPR08.pdf)

* [Learning real-time Prespective patch rectification](http://cvlabwww.epfl.ch/~lepetit/papers/hinterstoisser_ijcv10.pdf)

* [Deeper understanding of the homography decomposition for vision-based contro](https://hal.archives-ouvertes.fr/file/index/docid/174739/filename/RR-6303.pdf)

* [Practical Planar Metric Rectification](https://pdfs.semanticscholar.org/d9db/8fe72f14d17e40f0967785f1a1a4724966c9.pdf?_ga=1.239100551.546000381.1480911089)

* [Homography-Based Planar Mapping and Tracking for Mobile Phones](https://pdfs.semanticscholar.org/d608/be8c80dc8ab048e7fec7ad4c31adc3cc944d.pdf)

* [Pose Estimation for Augmented Reality: A Hands-On Survey](https://hal.inria.fr/hal-01246370/file/survey-ieee-v2.pdf)

## Lecture resource

* [COS 429 - Computer Vision](http://www.cs.princeton.edu/courses/archive/fall16/cos429/outline.html)

* [Structure from Motion](http://mi.eng.cam.ac.uk/~cipolla/publications/contributionToEditedBook/2008-SFM-chapters.pdf)

* [Binary Decision Diagram](https://www.cs.cmu.edu/~fp/courses/15122-f10/lectures/19-bdds.pdf)

* [FERN keypoint recognition](http://cmp.felk.cvut.cz/ftp/articles/svoboda/Derner-TR-2010-16.pdf)

* [Binary Image Analysis](https://courses.cs.washington.edu/courses/cse576/book/ch3.pdf)

* [Computer Vision course from University of Washington](https://courses.cs.washington.edu/courses/cse576/book/)

* [FERNs: Matching as Classification by Chen Feng](http://web.eecs.umich.edu/~silvio/teaching/EECS598_2010/slides/11_09_Chen.pdf)

* [Decision Tree - Classification](http://www.saedsayad.com/decision_tree.htm)

* [Bag of word for visual categorisation](https://gilscvblog.com/2013/08/23/bag-of-words-models-for-visual-categorization/)

* [simple supervised learning part 3: should i read it? the naive bayes method](http://matpalm.com/rss.feed/p3/)

* [v1: semi supervised naive bayes](http://matpalm.com/semi_supervised_naive_bayes/semi_supervised_bayes.html)

* [Understand homogenous coordinate system](http://www.songho.ca/math/homogeneous/homogeneous.html)

* [TLD（Tracking-Learning-Detection）学习与源码理解之（一](http://blog.csdn.net/zouxy09/article/details/7893011)

* [Learning Image patch similarity](http://ttic.uchicago.edu/~gregory/thesis/thesisChapter6.pdf)

## Development library

* [Theia Lirary](http://www.theia-sfm.org/index.html)

* [MATLAB and Octave Functions for Computer Vision and Image Processing](http://www.peterkovesi.com/matlabfns/)

* [dlib](http://dlib.net/)

## Stackoverflow

* [A simple explanation of Naive Bayes Classification](http://stackoverflow.com/questions/10059594/a-simple-explanation-of-naive-bayes-classification)

* [Drawing rectangle or line using mouse events in open cv using python](http://stackoverflow.com/questions/22140880/drawing-rectangle-or-line-using-mouse-events-in-open-cv-using-python)

* [Binary robust independent elementary features (“BRIEF”) understanding](https://dsp.stackexchange.com/questions/1305/binary-robust-independent-elementary-features-brief-understanding)

## Sample project

* [Markerless Augmented Reality](http://users.csc.calpoly.edu/~zwood/teaching/csc572/final11/geddingt/)

* [Smooth Panorama Stitching With Lie Algebras](http://pages.cs.wisc.edu/~lizhang/courses/cs766-2008f/projects/mosaic/students/mikola/)