Opencv

install opencv

 * opencv install script
 * https://gist.github.com/melvincabatuan/bcc21c9523b461e236fa889e556b2fe9 opencv install with cmake
 * https://gist.github.com/CorcovadoMing/ad7fde186287af261694

blas and lapack

 * https://www.youtube.com/watch?v=Wp0cHUiOHTQ BLAS and LAPACK are linear algebra packages
 * https://www.youtube.com/watch?v=6U5bDOwOK0c How to build LAPACK with cmake
 * http://www.netlib.org/lapack/
 * http://public.kitware.com/pipermail/cmake/2012-April/049817.html specify lapack directories.
 * http://www.openblas.net/, git clone https://github.com/xianyi/OpenBLAS.git Just type make to compile the library. https://github.com/cmr/openblas-src/issues/5 compiling errors.
 * sudo apt-get gfortran liblapack-dev libblas-dev libopenblas-dev libblas-dev liblapack-dev libopenblas-base libopenblas-dev
 * sudo apt-get install liblapack-dev

Itseez
https://github.com/Itseez/gtc-2015-lab Jetson tegra cpu

https://github.com/Itseez/opencv_for_ios_book_samples opencv book coding examples solution

http://elinux.org/Main_Page  embedded linux and boards supported

http://roboticssamy.blogspot.com robot balancing

v4l

 * sudo apt-get install v4l-utils
 * http://www.techytalk.info/webcam-settings-control-ubuntu-fedora-linux-operating-system-cli/

Authors

 * Derek Molloy beaglebone code v4l-tcl.c file scripting usb camera, mpeg4 compression etc.
 * pyimagesearch.com
 * https://github.com/tesseract-ocr/tesseract/wiki OCR

Yuki nagai
https://www.youtube.com/watch?v=pj-QuE6pdEQ The red bounding box is "Boosting" result, green is "MIL", blue is "TLD", black is "Medianflow", and pink is "KCF". Tracking code: Dataset and evaluation code: Evaluation results:
 * http://cvlab.hanyang.ac.kr/tracker_benchmark/
 * https://arxiv.org/abs/1404.7584 High-Speed Tracking with Kernelized Correlation Filters
 * https://github.com/yuukicammy/opencv_tracker_performance_test/blob/master/opencv_tracker/dev/src/main_opencv_trackeing.cpp
 * https://sites.google.com/site/trackerbenchmark/benchmarks/v10
 * https://github.com/yuukicammy/opencv_tracker_performance_test/tree/master/tracker_benchmark_v1.0/figs/overall/OpenCV
 * https://github.com/yuukicammy/struck  Struck: Structured Output Tracking with Kernels http://www.samhare.net/research/struck
 * http://eigen.tuxfamily.org

Zdenek Kalal
http://www.gnebehay.com/cmt (OpenTLD) Clustering of Static-Adaptive Correspondences for Deformable Object Tracking (CMT) is an award-winning object tracking algorithm, initially published under the name Consensus-based Tracking and Matching of Keypoints for Object Tracking at the Winter Conference on Applications of Computer Vision 2014, where it received the Best Paper Award. A more detailed paper was published at the Conference on Computer Vision and Pattern Recognition 2015. CMT is able to track a wide variety of object classes in a multitude of scenes without the need of adapting the algorithm to the concrete scenario in any way. Experiments have shown that CMT is able to achieve excellent results on a dataset that is as large as 77 sequences. A C++ implementation (CppMT) is freely available under the BSD license, meaning that you can basically do with the code whatever you want. Additionally, the original Python research code is still available for reference.
 * https://github.com/gnebehay/CppMT Newer algorithm preferred over Kalal's previous OpenTLD.

papers
https://www.researchgate.net/publication/279057771_Expert_Video-Surveillance_System_for_Real-Time_Detection_of_Suspicious_Behaviors_in_Shopping_Malls

http://www4.comp.polyu.edu.hk/~cslzhang/CT/CT.htm Real-time Compressive Tracking and c++ code

forum questions
http://stackoverflow.com/questions/28619037/opencv-where-is-tracking-hpp itzees repository

http://stackoverflow.com/questions/36254452/counting-cars-opencv-python-issue?rq=1 python counting cars by http://stackoverflow.com/users/3962537/dan-ma%c5%a1ek

Neural nets
https://github.com/udacity/CarND-TensorFlow-L2 Udacity self driving car, open source.

counting cars
Chris Dahms

links
http://stackoverflow.com/questions/36117123/cmake-error-that-i-do-not-understand/36117181#36117181 cmake error and snake game. c++ tutor.
 * simplecv vision framework for vision applications, acccess OpenCV  without having to first learn about bit depths, file formats, color spaces, buffer management, eigenvalues, or matrix versus bitmap storage. This is computer vision made easy.
 * https://ukoethe.github.io/vigra/ Vision with Generic Algorithms library
 * Ffmpeg, Libccv, Segnet , Caffe berkeley vision , OpenKcam , GPU ,
 * KLT vision
 * https://groups.google.com/forum/?hl=en#!forum/visual-tracking Google image groups.
 * https://www.researchgate.net/post/Which_is_the_best_tracking_algorithm_available which algorithm to use.
 * http://www.thine.co.jp/en/products/num_details/THP7312.html THine's ISP is an image processing engine for a digital camera. The pipelined image processing engine is possible to high speed processing. Auto Exposure / Auto Focus / Auto White Balance can be done by the special circuit. You can get the best picture quality in each CMOS sensor by using THine's ISP with our original noise reduction and gamma correction. THP7312 supports RGB+IR and alternate row HDR sensors. And THP7312 added De-fog function for advanced applications. Additionally RGB and IR images output simultaneously by MIPI virtual channel. https://www.e-consystems.com/Cypress-CX3-THine-ISP-13MP-RDK.asp development kit Ascella (See3CAM_CX3ISPRDK) is an USB Video Class (UVC) USB 3.0 reference design kit developed using Cypress® Semiconductors' EZ-USB® CX3™ and THine® Electronics, Inc.'s THP7312 Image Signal Processor (ISP). This kit uses 13MP Autofocus camera module based on OmniVision OV13850 CMOS image sensor. The Cypress EZ-USB® CX3 is a USB 3.0 peripheral controller that enables developers to add USB 3.0 connectivity with any image sensor compliant with Mobile Industry Processor Interface (MIPI) Camera Serial Interface Type 2 (CSI-2) standard. e-con has already developed a Reference Design Kit called Denebola using this CX3 controller with a OV5640 SoC image sensor which does not require any external ISP.  The Ascella kit leverages the THP7312 ISP to bring out the best-in-class video quality at UltraHD 4k2k, 1080p and 720p resolutions and 13MP Still Image resolution from the 13MP Autofocus camera.