20170817 17:34:05 0500  commented question  Why am I Getting distorted images after sending them from C# to OpenCV in C++? We don't support C#, but have you checked the pitch? IE: the first image is 1414 pixels wide. Perhaps there is a gap in the memory, and each row is 1424 apart or something. 
20170816 20:16:02 0500  answered a question  What's the best method for tracking identical objects? This is an excellent use of the Kalman Filter. It can estimate the position and velocity of the balls, predict where they will be in the future, and give you a confidence interval of how certain the estimates are. As for which detection is which track, that is called track association. You should be able to get away with something simple like the Hungarian Algorithm and the distance from the Kalman Filter's prediction. The methods can become amazingly complicated though, as you add more constraints. 
20170816 17:23:01 0500  commented question  OpenCV in use cases requiring millisecondlevel precision I probably wouldn't use one of the built in trackers at all. Just use color thresholding to separate out the three colors, and then do your own processing of the results. Since it's so simple and regular, you don't need anything that learns like KCF. 
20170815 07:32:13 0500  answered a question  Human skeleton extraction from depth data by using machine learning or neural network. Here is a link to the MPII Human Pose Database, which has a results page. The second best one has a link to a pretrained model. I don't know if you can load it into the new DNN module, but it does work if you use their democode. This doesn't use the depth data though. I'm not sure of a dataset that includes that as well. 
20170814 20:33:36 0500  commented question  Time to contact That looks to be a good plan based on what I've just read. http://opticflow.bu.edu/research/timetocontactestimation It's up to you to turn the optical flow into the size of an object. Which shouldn't be too hard. Do optical flow, then any pair of points you can calculate the expansion. Dense optical flow will let you average over the points in a window or a sampling around it, helping filter out outliers or things moving sideways. Expansion = (distance between points after flow  distance before flow) / (distance before flow). 
20170814 17:57:59 0500  answered a question  How can a single channel represent a color image? Fun fact, CV_8UC3 == 16. The function cv::imread takes an optional second parameter which is a flag from the enum cv::imreadmodes. In that enum, 16 == IMREAD_REDUCED_GRAYSCALE_2, which has the comment
Try removing that second parameter and see if it works better. 
20170811 07:31:43 0500  answered a question  cv::Mat_ vs std::vector cv::Mat_<> is a two dimensional structure. std::vector<> is a one dimensional structure. If you have a 2D shape, then go ahead and use Mat_. If you have a 1D shape, you can use either, unless you want it to change size (push_back, pop_back), in which case, use vector. 
20170810 18:58:02 0500  commented question  [Paid job] Multiview solvePnP routine gau ssg un+ew @ gma il. com Remove the spaces of course, and let me know when you see it so I can remove it before the spammers find it. 
20170808 22:46:36 0500  commented question  Obtain Camera Pose and camera real world position using SolvePnP C++ It's a fisheye camera, did you calibrate using the cv::fisheye::calibrate? 
20170729 13:15:29 0500  answered a question  Problem with exact measurement of tracking balls It's likely that your measurements are noisy, but if you've got more than 3, you can use something called a Kalman Filter. You can use this to get accurate estimates of noisy measurements. Set up the filter correctly, input the position of the ball every time you measure it, and read the sate for estimates of position, speed, and acceleration. It's beyond the scope of this forum to explain how to use it, but there are many tutorials on the internet, and the OpenCV syntax is explained in the documentation (linked above) and the kalman.cpp example. 
20170728 17:03:27 0500  commented question  Triangulating points into worldspace, and using in solvePnp. I don't think you need the Tran.inv(), and the function cv::transform will do it to all the points in the list at once. 
20170727 23:03:56 0500  answered a question  How to capture Video from Firewire Basler scout Camera? This forum supports OpenCV only. As this is not an OpenCV problem, you're probably better off contacting whoever provided the PYLON App for support. Good Luck! 
20170727 17:49:21 0500  commented question  How to pass an already stored data in GPU by GpuMat to a kernel As the documentation says 
20170727 00:41:21 0500  answered a question  Not understanding how calcOpticalFlowPyrLK outputs found points You are correct. As for what is in fb if status is not 1, it is undefined. It's likely the last value that failed the validity check, but it could also be the starting value, or anything else, including NaN. Do not use these values. 
20170726 18:00:14 0500  commented question  Triangulating points into worldspace, and using in solvePnp. Ok, your updatePMatrix is wrong (I think). Instead of changing the P matrix, keep what you calibrated. Instead you should just transform the points at the end of triangulateCv. Just use the rvec and tvec from solvePnP directly. Sorry, life happened. I might have some time this weekend to do a little demo thing to test this in. 
20170720 21:56:35 0500  commented answer  Match 2d keypoints to 3d Triangulated points using three sets of descriptors? Yeah, and include a sample of your image points, rvecs and tvecs so others can play with them. 
20170720 18:05:36 0500  commented answer  Match 2d keypoints to 3d Triangulated points using three sets of descriptors? You shouldn't need to invert your tvec and rvec, I don't think. I don't think you need that at any point. 
20170716 19:52:12 0500  commented answer  Match 2d keypoints to 3d Triangulated points using three sets of descriptors? The last function you should just transform the points by the current rvec, tvec. Turn it into a projection matrix (The 4x3 thing, the 3x3 rotation mat, then the last column is the tvec) Then use the transform function to apply it to all the points in the list. I think that's all. 
20170714 18:45:39 0500  commented answer  Match 2d keypoints to 3d Triangulated points using three sets of descriptors? Ok, I need to get long, so I'm going to edit the answer. 
20170714 17:12:41 0500  commented question  calculate matrix rotation translation with two cameras And what do the matrices H and R represent? I'm not familiar with any H matrix in the context of two cameras. 
20170711 18:38:37 0500  commented question  Reading PNG images not giving alpha values Are you on windows? Right click on the file>Properties>Details>Bit Depth and tell us what it is. On Ubuntu there's something called pnginfo, but I admit to never having used it. 
20170711 17:54:01 0500  commented answer  Match 2d keypoints to 3d Triangulated points using three sets of descriptors? So you do realize, that each iteration of the loop sees a new copy of the tempDescriptor Mat? You need to declare that outside the loop. 
20170709 17:41:18 0500  commented answer  Match 2d keypoints to 3d Triangulated points using three sets of descriptors? No, not that loop. In the frame1 loop, where you do the push_backs. You need to also save the desc that matches the keypoint. 
20170708 17:20:01 0500  commented answer  Match 2d keypoints to 3d Triangulated points using three sets of descriptors? You also need to filter the descriptors the same way you do the key points. So you're removing key points, but not keeping track of which keypoint matches which descriptor. If you also remove the descriptors at the same time, and then match the smaller list against new frames, that should work. 
20170708 17:14:12 0500  commented answer  OpenCV filter that allows filter taking two images as Base Regrettably, no. As best I can tell, none of them have a Java API, though it might be possible for you to add them. I have no idea what is required to make a function work in the OpenCV Java API. 
20170707 16:13:44 0500  answered a question  OpenCV filter that allows filter taking two images as Base What you are looking for is in ximgproc::filters. Unfortunately, no Java version. Personally, I prefer THIS filter. It is about as fast as the guided filter, but more accurate. It's the same algorithm used in the DisparityWLS, but you can simplify it and speed it up for normal images. 
20170706 17:56:00 0500  answered a question  Match 2d keypoints to 3d Triangulated points using three sets of descriptors? Well, objectPointsTri has a 1<>1 mapping with descCurrent. And, matchPoints is (query, train), if you didn't reverse the parameters. So that means the trainIdx property of the match has the index in both descCurrent and objectPointsTri. EDIT: Ok, to understand what you're doing, you need to break this apart into functions. You have one long block and that's probably part of why you're having trouble. The functions you need that I'm not going to write for you are (and you already have some of these)
So each set of frames produces a list of keypoints for L an R, one for each match, in order, A matching set of Descriptors for L, and 3dPts, one for each match, in the same order. Everything after the first matches the new L to the old L, and filters by those matches. Then those get used for solvePnp. After the first frame you have to adjust the 3dPoints, because triangulate assumes the camera is the coordinate reference, but we know it isn't, so you have to adjust for that. 
20170706 17:41:27 0500  answered a question  Rolling Guidance Filter HERE is the paper that describes the rolling guidance filter and particularly how it differs from the Gaussian and a few other edge aware filters. 
20170704 15:07:18 0500  answered a question  Tracking existing Keypoints across a video? calcOpticalFlowPyrLK will track a point or set of points from frame to frame. This is particularly good for small motions per frame, where the appearance doesn't change much between frames. You can of course augment this by using a descriptor such as ORB, SURF, SIFT or similar to create descriptors for each point and match those as well to make sure the correct point is found. 
20170704 11:45:18 0500  commented answer  Rodrigues rotation Like I said, I'm not sure what it is representing, but it is not the same thing and cannot be substituted. K (capital) is very much not the same as k (not capital). It may look similar, but if you use it without understanding, you'll use it wrong. Specifically, K^2 v = k cross (k cross v), but the top equation has k (k dot v) in the third term. 
20170702 21:19:41 0500  commented question  Why vGPU (Tesla K80) on Google cloud slower than GTX940M on T460P I'm not actually sure there is a GPU portion for that classifier... The nvidiasmi report, I'm not very familiar with it, but isn't that just the default process? It's not using it for computation? 
20170702 19:05:28 0500  commented answer  Rodrigues rotation Looking at HERE, still a cos involved. Not sure what the Matrix Notation there represents, but that's definitely not the formula you use. 
20170702 17:07:14 0500  answered a question  Rodrigues rotation I think the relevant bit is up the page a bit. In the Statement section. There you see exactly the equation you ask about. 
20170630 17:06:26 0500  commented answer  Retrieve yaw, pitch, roll from rvec To be clear, there is no such thing as a "rotation matrix for a xy'z" TaitBryan sequence". There is only a rotation matrix. By definition, all euler angles describing an orientation produce a particular rotation matrix. If someone gives you three numbers and says "Here's the euler angles for a rotation", you must ask which order they are, and you'll get a response from that table (or one like it). If someone gives you a rotation matrix, you're done. You already know everything about the rotation. 
20170630 16:59:23 0500  commented answer  Retrieve yaw, pitch, roll from rvec You are misunderstanding what that shows. All of those are valid decompositions and produce valid euler angles, and all start from the same rotation matrix. They merely produce different sets of euler angles. One of those is equivalent to yaw pitch roll, the others are something else. But they all are the same rotation matrix, and the same orientation in space. 
20170629 20:13:08 0500  answered a question  Fast Matching Pyramids Rotationinvariance You can't really "downsample" rotation. At least, not if you're just trying to find the object. If you need to find the specific rotation that is best, and template matching can find the object while the rotation is incorrect by a significant amount, then you rotate the image with big steps, doing template matching on each one. The around the best angle, do finer steps and repeat until it's precise enough. 
20170629 20:03:36 0500  answered a question  Place data of Mat at a specific memoryarea pointed to by a pointer If you map the pointer into a Mat, and the Mat is the exact size and type of what you are copying, you can simply use the copyTo function. copyTo is the only reliable way to do this. Some functions will store their result into it, but not all, and some depend on the other input parameters for where they store it. 
20170629 19:59:13 0500  commented question  Overlaying masked image over another? There are plenty of perfectly good reasons to do this berak. No reason to be rude. 
20170629 19:56:11 0500  answered a question  Overlaying masked image over another? The copyTo function takes a mask as a parameter. 
20170629 19:52:38 0500  answered a question  Retrieve yaw, pitch, roll from rvec The rotation matrix is the rotation matrix is the rotation matrix. There is only one. The decomposition into three euler angles is where the rotation order changes. You can go from the rotation matrix to any of those angle orders, you just need to decide which order is what you need. Remember, the camera is looking up the z axis. So yaw rotates the image, pitch turns the image to the left and right, and roll is up and down in the image. (assuming all the other angles are 0, combining them is less simple) 
20170629 17:49:22 0500  commented answer  Using solvePnp on a video stream with changing points. Ah, I see the problem. You need to use triangulate points using the projection matrices from the previous frame. Secondly, don't do a separate solvePnP for both cameras, or they'll start drifting. Do it just for the one that calibrates as the origin, then apply the transformation you get for the second camera to the results from solvePnP to get it's location. Thirdly, each frame, use the results from solvePnP to create new projection mats to use with triangulate points. 
20170628 17:38:17 0500  commented answer  Using solvePnp on a video stream with changing points. Do you have an external reference that you use as 0,0,0? If not, then there's no true difference between camera and object space. Your code is too fragmented for me to follow the data flow, but it should go like this:

20170627 17:31:19 0500  commented question  Retrieve yaw, pitch, roll from rvec Ah, no. By definition, pitch is y and roll is x. Always has been. Check the link in your answer. 
20170627 07:32:59 0500  commented answer  Using solvePnp on a video stream with changing points. Ok, let's debug this from the beginning. Is the first set of points correct? IE, the first frame, you are at (0,0,0), and you see all these points out in the world. Are they approximately correct? All positive z, and they show up in the right place on the image when you use projectPoints? 
20170626 17:39:45 0500  answered a question  Using solvePnp on a video stream with changing points. 
20170625 16:30:08 0500  commented question  Retrieve yaw, pitch, roll from rvec Nope, I just worked it out. The yaw 90 puts the camera x = y, camera y = x, camera z = z Then Roll 90 then rotates around the camera x so you get camera x = y, camera y = z, camera z = x, which is what you want. If you did pitch 90, you would be rotating around the y, and would get camera x = z. Any yaw and a pitch of 90 gives you your camera x = down, which would mean your camera is turned so the right side of the image is down. 
20170624 19:41:43 0500  answered a question  Calculate x distance to line from edge at middle of y? Well, this is more geometry than computer vision, but here you go. Turn your line into the form y = m*x+b. If you don't know how, use the example to get two points on the line, and solve. Then x = (yb)/m, where y = rows/2 
20170623 16:08:52 0500  commented question  Retrieve yaw, pitch, roll from rvec Hmm, nope. A camera looking east would have a yaw component of magnitude 90. Positive or negative, I'm not sure without coloring my fingers, but I can tell it's needed. 
20170622 22:35:31 0500  commented question  Retrieve yaw, pitch, roll from rvec The rotation matrix is independent of operation and stores the complete rotational information. When decomposing it to euler angles you choose the order of those rotations. The camera coordinates are x is right, y is down, z is out into the world. The world coordinates are defined by the points you use solvePnP with. 