Chessboard Pdf Open Cv Face Detection

Basics This is going to be a small section. During the last session on camera calibration, you have found the camera matrix, distortion coefficients etc. Given a pattern image, we can utilize the above information to calculate its pose, or how the object is situated in space, like how it is rotated, how it is displaced etc.

For a planar object, we can assume Z=0, such that, the problem now becomes how camera is placed in space to see our pattern image. So, if we know how the object lies in the space, we can draw some 2D diagrams in it to simulate the 3D effect. Let’s see how to do it. Our problem is, we want to draw our 3D coordinate axis (X, Y, Z axes) on our chessboard’s first corner. X axis in blue color, Y axis in green color and Z axis in red color. So in-effect, Z axis should feel like it is perpendicular to our chessboard plane.

Project includes writing code in C++ using OpenCV libraries for calibrating cameras, and recognition for tracking 3D object. Figure 2.5: Chessboard used for calibration of stereo cameras. Figure 2.6: Two USB. Automated monitoring systems, including face and object recognition. Detection and identification of.

First, let’s load the camera matrix and distortion coefficients from the previous calibration result. Def draw ( img, corners, imgpts ): corner = tuple ( corners [ 0 ]. Ravel ()) img = cv2. Line ( img, corner, tuple ( imgpts [ 0 ]. Ravel ()), ( 255, 0, 0 ), 5 ) img = cv2. Line ( img, corner, tuple ( imgpts [ 1 ].

Ravel ()), ( 0, 255, 0 ), 5 ) img = cv2. Line ( img, corner, tuple ( imgpts [ 2 ]. Ravel ()), ( 0, 0, 255 ), 5 ) return img Then as in previous case, we create termination criteria, object points (3D points of corners in chessboard) and axis points. Axis points are points in 3D space for drawing the axis. We draw axis of length 3 (units will be in terms of chess square size since we calibrated based on that size).

So our X axis is drawn from (0,0,0) to (3,0,0), so for Y axis. For Z axis, it is drawn from (0,0,0) to (0,0,-3). Negative denotes it is drawn towards the camera. Criteria = ( cv2. TERM_CRITERIA_EPS + cv2. TERM_CRITERIA_MAX_ITER, 30, 0.001 ) objp = np.

Zeros (( 6 * 7, 3 ), np. Float32 ) objp [:,: 2 ] = np.

Mgrid [ 0: 7, 0: 6 ]. Reshape ( - 1, 2 ) axis = np.

Float32 ([[ 3, 0, 0 ], [ 0, 3, 0 ], [ 0, 0, - 3 ]]). Reshape ( - 1, 3 ) Now, as usual, we load each image. Search for 7x6 grid. If found, we refine it with subcorner pixels.

Then to calculate the rotation and translation, we use the function, cv2.solvePnPRansac(). Once we those transformation matrices, we use them to project our axis points to the image plane. In simple words, we find the points on image plane corresponding to each of (3,0,0),(0,3,0),(0,0,3) in 3D space. Once we get them, we draw lines from the first corner to each of these points using our draw() function. For fname in glob. Glob ( 'left*.jpg' ): img = cv2.

Imread ( fname ) gray = cv2. CvtColor ( img, cv2. COLOR_BGR2GRAY ) ret, corners = cv2. FindChessboardCorners ( gray, ( 7, 6 ), None ) if ret == True: corners2 = cv2. CornerSubPix ( gray, corners,( 11, 11 ),( - 1, - 1 ), criteria ) # Find the rotation and translation vectors. Rvecs, tvecs, inliers = cv2. SolvePnPRansac ( objp, corners2, mtx, dist ) # project 3D points to image plane imgpts, jac = cv2.

ProjectPoints ( axis, rvecs, tvecs, mtx, dist ) img = draw ( img, corners2, imgpts ) cv2. Imshow ( 'img', img ) k = cv2. WaitKey ( 0 ) & 0xff if k == 's': cv2. Imwrite ( fname [: 6 ] + '.png', img ) cv2. DestroyAllWindows () See some results below.

Notice that each axis is 3 squares long.. Def draw ( img, corners, imgpts ): imgpts = np. Int32 ( imgpts ).

Reshape ( - 1, 2 ) # draw ground floor in green img = cv2. DrawContours ( img, [ imgpts [: 4 ]], - 1,( 0, 255, 0 ), - 3 ) # draw pillars in blue color for i, j in zip ( range ( 4 ), range ( 4, 8 )): img = cv2. Line ( img, tuple ( imgpts [ i ]), tuple ( imgpts [ j ]),( 255 ), 3 ) # draw top layer in red color img = cv2. DrawContours ( img, [ imgpts [ 4:]], - 1,( 0, 0, 255 ), 3 ) return img Modified axis points. They are the 8 corners of a cube in 3D space.

2015 OpenCV Meeting notes for 2015 year Template is at 2015-07-21 Agenda • SoW • GSoC • Book Minutes • The proposal is based on the developed table • We take a group of functions or similar functions, • we put fastCV calls for these functions into OpenCV, • We detect fastCV at compile stage and use it if it is there, • we run accuracy tests, performance tests, • add missing performance and accuracy test, • we disable functions that fail accuracy tests that cannot be solved in an easy way, • if performance drops — we disable the use of that function. • Produce performance report • 6K or more • GSoC most projects moving along • Book — Go Vadim go. Vadim After quite intensive May & June with 3.0 release and CVPR July has been quite slow month. This is the joint report for 4 weeks. OpenCV: • We plan to migrate our git repository, bug tracker and wiki to github. This should solve completely rare but still possible bandwidth and backup problems, and would allow us to get rid of code.opencv.org and associated maintenance efforts. That is basically within the common trend “everything’s in the cloud”.

• Maksim developed necessary scripts to convert all the wiki pages and all the bug tracker issues from chiliproject (used by code.opencv.org) to github format. For wiki github uses markdown (and wiki is stored as git repository, so we have all the history!). • This is the converted wiki: • This is the converted bug tracker database: • The repository conversion is trivial – we will just modify our pullrequest.opencv.org engine to push the patches directly to github instead of github repository. • The actual conversion is expected in the end of this week or next week • Also Maksim has put beta version of OpenCV Android Manager to GooglePlay. With 3.0 we offered standalone.apk with the manager for local tests, now it’s available from GooglePlay. Here is the announcement: • Alexander A made several improvements in buildbot, some of which required patching buildbot code. Now several steps are executed in parallel, just like parallel make builds multiple files in parallel: • Parallel buildbot: This is realtime web output from builtbot and the currently executed jobs are displayed in yellow.

It should dramatically improve the testing speed, because most tests are single-threaded. • Some more useful improvements in the infrastructure: ffmpeg bindings for Windows (opencv_ffmpeg*.dll) are now cross-compiled on Linux (apparently, mingw on Linux is much more stable than native Windows version) and the binaries are now placed in a separate opencv_3rdparty repository. • Alexander Kalistratov finished parallel motion jpeg encoder and at once tested pthread-based parallel for, which he implemented earlier.

The parallel encoder demonstrates quite good scalability – 3x faster encoding on 4-core machine. Why we spent that much time on the motion jpeg codec? Because on mobile devices it’s often much more convenient to capture and store various videos and then play with the videos on desktop using a convenient IDE. It’s true that Android and iOS may encode video using H264, but usually the quality of individual frames is quite low. As opposite to that, motion jpeg does not use any motion prediction, and so fast motion is captured very well there are no any other compression artefacts.

Besides, this thing is completely cross-platform. Even single-threaded codec was able to encode HD (720p) video @30fps.

Multi-threaded codec can capture FullHD @30fps. GSoC: • Midterm evaluation is over. 14/15 students have passed it. One of Vadim’s student failed midterm because of insufficient performance. • Maksim’s student Alexander Bokov mostly finished his “bonus” task, as he’s already done with the planned activities.

He implemented draft version of parallel 3-directional SGBM. Such variant of SGBM is 2.5-3x faster than single-threaded 5-directional SGBM and yet still delivers decent quality of the depth map (in the image below are multiple cases from middlebury: left image, result from 5-dir single-threaded SGBM, result from 3-dir multi-threaded SGBM: • Vadim’s student Lluis Gomez prepared preliminary implementation CNN-based OCR algorithm, a part of long-term text detection project in OpenCV. The results are pretty good, comparable with Tesseract, as long as 1) the words are well segmented and 2) there is limited dictionary used (say, a few hundreds words). The speed is quite low, though. Now Lluis is preparing detailed comparison with Tesseract and tries to reuse existing text module functionality to properly segment words in automatic way. About 40 PR’s have been merged since the end of June. OpenCV Plans: • Finish migration to github.

• In July-August try to extend OpenCV HAL to several dozens of functions, at least. Numl: • Still working on the type checker. Adding classes and other smaller syntax extensions required quite a lot of refactoring work. Now the type checker is almost complete, and within a week or two it should be finihsed and tested.

• Alexander A will participate part-time in the numl compiler activities. We really need to speedup and try to make working compiler + runtime + basic standard library by the end of summer.

• Here is the current state of the compiler: • Numl Plans: • Finish the type checker, proceed with K-normalization and other parts. Misc: • Maksim was on vacation for 2 weeks in the first half of July. • Alexander Kalistratov finished his internship at OpenCV dev team and moved to another team within Itseez.

Good job, Alexander, thank you and all the best to you! Action Items Gary •. Vadim • Ask Alexander Shishkov about how to get statistics for websites Grace •. 2015-06-30 Agenda • GSoC ratings • Book • Qualcomm • Awards Minutes • GSoC need pull requests in • See waterfall — If pull request is building: • Fill out your evaluations here: • How to do a pull request: • Github for opencv_contrib: • Qualcomm • Initial assesment of complexity for qualcomm • SOW needed from us and to ping them • Book • Next couple of chapters • Need to distribute awards • Reports •. Vadim Action Items Gary • Ping qualcomm. SOW Vincent •. Vadim • Reminders to Vlad adn Seon-Wook • Book Grace • Collect names and emails of winners 2015-06-23 Agenda • GSoC midterm grading starts Friday June 26, must be complete by Friday July 3 • • Contest.

Have to contact, pay out. Waiting on Intel’s funding • • Book Minutes Contest • Grace getting list of email contacts of the winners. • Intel Invoice was sent in, probably 25 days, but money to pay now exists. Schwag • We have enough money to order some more scwag GSoC Progress. Need Pull requests (don’t have to be complete) to pass by July 3rd • Mentors • opencv-gsoc2015-mentors • Students • opencv-gsoc2015-students • Pull Request In Antonella Cascitelli – Vladimir Tyan (terran.itx@gmail.com): TLD improvements – • Pull Request In Bo Li – Baisheng Lai (laibaisheng@gmail.com). Omnidirectional Cameras Calibration and Stereo 3D Reconstruction.

• No Pull Request Vincent Rabaud – Edgar Riba (edgar.riba@gmail.com). Structure From Motion module. • Pull Request In Bence Magyar – Jiaolong Xu (jiaolongxu@gmail.com).

Improving PBM in OpenCV. • Pull Request In Fernando J.

Iglesias Garcia – Laksono Kurnianggoro (kurnianggoro@gmail.com). Real-time Multi-object Tracking using Kernelized Correlation Filter.

• No Pull Request, but previously Vadim Pisarevsky – Lluis Gomez (lgomez@cvc.uab.es). Improve and expand Scene Text Detection module in OpenCV. • No Pull Request Michael Harville, Gary Bradski – Naoto Hieda (micuat@gmail.com).

Projection mapping (Projected Augmented Reality). • Pull Request In Sergei.Nosov@itseez.com – Mircea Paul Muresan (mmp_mircea@yahoo.com).

Stereo correspondence improvements. Can not mentor the student. Does anyone want to take one?] • Pull Request In Delia, Stefano Fabri, Claudia Rapuano – RobertaRavanelli (roberta.ravanelli@uniroma1.it). Structured-Light System Calibration for OpenCV. • “done” Pull Maksim Shabunin – Alexander Bokov (sbokov01@gmail.com). Recent advances in edge-aware filtering. • No Pull Request Prasanna, Gary Bradski – Sergio Garrido (sgarrido2011@gmail.com).

Charuco board: Chessboard+ArUco for camera calibration. • No Pull Request Alexander Bovyrin – Vlad Shakhuro (shahurik@gmail.com).

ICF detector improvements. • Pull Request In Vadim Pisarevsky – Seon-Wook Park (seon.wook@swook.net).

Real-time image preprocessing on ARM. Juki Pm 1 Keygen Idm. • Pull Request In Anatoly Baksheev, Douglas Lee – Vitaliy Lyudvichenko (ludv1x@yandex.ru). Implementation of universal interface for deep neural network frameworks. • Pull Request In Manuele Tamburrano, Stefano Fabri – Yida Wang (wangyida37@gmail.com).

Deep Learning & GPU Implementation Proposal. Book • Next 2 weeks • Vadim for form, Gary for edits Reports Vadim OpenCV: • OpenCV 3.0 is out! The announce has been published • Prepared and delivered OpenCV 3.0 tutorial at CVPR 2015. The slides are available here: • (Introduction to OpenCV 3.0) • (Speeding up with OpenCV 3.0) • (Some cool features in 3.0 and opencv_contrib). • There has been also test run of the practical session using web-OpenCV. With more time and care the approach could be very successful. Overall, the tutorial went pretty good.

• Over 30 PRs have been merged since 3.0 final; About a dozen of bugs have been fixed • ffmpeg wrapper got H264 support via BSD openh264 lib from Cisco. As opposite to GPLed x264, this new feature gives OpenCV users more liberal way to encode videos with h264. • Android support is still being improved. The final version of OpenCV Manager for Android should be ready next week and then after more testing it will be published at Google Play.

• GSoC projects go very well. • Maksim’s student submitted all the PR’s with edge-aware filters for disparity map. Basically, he mostly finished the planned GSoC program and will now look at possible StereoSGBM improvements.

• Lluis Gomez (mentored by Vadim) is working on self-contained text recognition tool. It already gives promising results and the PR should be ready by midterm. • Seon-Wook Park’s patch with fast improved grayworld white balance algorithm has been merged. The initial version of spatialGradient function (already twice faster than 2xSobel) is ready and is being further improved now. • Several other projects demonstrated good progress as well: omni-directional camera calibration, binary features for stereo correspondence improvement, deep learning support etc. OpenCV Plans: • During July we plan to migrate our repository to github, together with wiki and the bug tracker. • Alexander is working on speeding up buildbot testing infrastructure, we plan to speedup build and especially the regression tests by running multiple jobs.

• Other multiple improvements in buildbot are planned, e.g. Adding regression tests for opencv_contrib to the precommit builders. Numl: • Resumed work on the compiler. The language syntax has been extended to something like 99% of the initially planned features – added classes, interfaces, array comprehensions, type cast operation, string interpolations etc. Some other elements have been refined too. Of course, extended syntax requires substantial modification of all the compiler stages. For now the lexer, parser, AST and the pretty printer have been updated.

Started work on extending one of the most complex part – the type checker. The latest snapshot can be found at • Numl Plans: • Update the type checker, proceed with K-normalization and other parts. Action Items Gary •.

2015-06-16 Agenda • GSoC • Contest • NUML • Book Minutes • GSoC • Submitted PO • This time won’t wait for mentor conference travel receipts. Will pay promptly and bill the remainder after travel is in. • Contest • Submitted payment request to Intel. Then can pay out awards • Next • OpenCV contrib, adding regression tests.

5 machines to run tests (2 arm, 1 mac, 1 linux, 1 windows). Want to optimize the regression tests • Need to update the cheetsheet. Need to reference doxygen. • NUML • High level bugs only • Matix expressions easy • Can convolution be easily expressed?

• Book • Ch 1-3 done • Where should OpenCL, IPP (free) • Umat has to be used carefully, because overhead makes small matrices much slower. Only UMat large images • parallel for • OpenCL • Machine learning is hardest, Ch13 will wait. But interface has changed a lot. • Looking at 50 pull requests Reports •. Vadim Action Items Gary •.

2015-06-04 Agenda • OpenCV Contest • OpenCV People’s Choice Best Paper • Workshop • GSoC Minutes • OpenCV Contest • OpenCV People’s Choice Best Paper • Workshop • GSoC Reports OpenCV: • OpenCV 3.0 is ready. Very likely it will be packaged and released tomorrow. The number of closed bug reports exceeded 200.

Preliminary version of the changelog is here, as usual: • PR for the new Android OpenCV Manager (created by Maksim) is pending. It’s written in Java, it’s much simpler than the previous Manager (because it’s in Java and because it makes use of all the nover features of Android 4.x and Google Play). • pthread-based cv::parallel_for_ has been integrated. It passes all the tests.

• Slides for CVPR 2015 tutorial are in progress. The link to the draft version has been sent separately. • Alexander Alekhin more or less finished web-OpenCV app: users can choose one of pre-defined opencv samples, edit, run, see the result images, upload their own images as inputs. C/C++ and Python are supported. • played with 2 contributions out of 17 for the challenge ( LATCH binary descriptor and RHO algorithm for computing homography).

They both have been contributed to OpenCV and they both appear to be quite good algorithms. • GSoC: • there are first results already from Alexander Bokov (mentored by Maksim): • • text detection (Lluis Gomez, mentored by Vadim) – Lluis will finish and prepare PR on the simple CNN-based text recogniser. Right now we can only recognize text using 3rd-party Tesseract. • optimized for ARM image preprocessing (Seon-Wook Park, mentored by Vadim) – the student is working on optimized grayworld white balance implementation, will submit PR soon. • improved stereo correspondence using binary descriptors (Mircea Paul Muresan, mentored by Sergei Nosov) – the plans have been finalized, student started working on implementing simple dense binary descriptors (such as Census). OpenCV Plans: • Release OpenCV 3. Antipop Consortium Discography Downloads on this page. 0, publish announcement. • Add more material to the tutorial.

• After 3.0 release continue QA work - • add new builders to the buildbot, • extend existing (in particular, run some opencv_contrib tests), • repair Java tests, Numl: • not much progress on the numl during these 3 weeks. • The latest snapshot is at: • Action Items Gary •. 2015-05-26 Agenda • GSoC 2015 • CVPR tutorial • CVPR challenge • CVPR People’s Choice Best Paper Minutes • GSoC 2015 • Deep learning task, • Contacted author of paper • • • all the network protocal produced w/blender • All results will go continuously into opencv_contrib. Contrib is only tested on buildbot for master branch • • Add ppt slides to google drive and send Vadim the links. • 0.45: intro talk. • 0.05: future directions • 1h: Vadim, internal. HAL, GMat, faster, since.

• 1h: the new API. Mat, Mat_, GMat, Algorithm, OpenCV2, imgproc, Python, (OpenCV3), • 1h: GSOC, inpainting, RGBD, tutorials. =>exercises: USB keys with OpenCV3,.debian • CVPR challenge • On last week we got 17 submissions on the Challenge in 5 categories: • tracking: 8 • image segmentation: 2 + 2 foreground detection • image registration: 3 • gesture recognition: 1 • object recognition: 1 • CVPR People’s Choice Best Paper • template for voting results • export results as xml files (but papers by unique ID) • need to get ID to papers, Grace will get from Terry Boult • big archive from Dmitry with 17 contributions Reports •. Vadim OpenCV: • The work on stabilization of OpenCV 3.0-pre continues.

During the past 3 weeks we’ve merged over 60 pull requests, closed ~150 bug reports! In particular, such areas as documentation, building and installation, python bindings, core, imgproc, features2d, calib3d have been improved. We’ve even fixed some 2-years-old, 3-years-old bugs. • We’ve also regenerated and uploaded the new 3.0rc Android package where some files were missing. • OpenCV 3.0 final is going to be released in the beginning of June, just before CVPR.