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2013-12-05 08:12:06 -0600 | answered a question | Human height estimation using a calibrated camera Hi there, start off with the article "Single-View Metrology: Algorithms and Applications" from Criminsi. You can find it here http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.83.1441&rep=rep1&type=pdf. The following article seems to implement a possible algorithm: http://www.mit.edu/~sysun/ComputerVision/SVM.pdf (I did not read it). This should give you a good starting point to find other articles. If you do not have access to a (digital) library, I recommend using scholar.google.com which typically gives me nice results (although not comparable to a professional library). Hope that helps. Case1 |
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2013-12-04 12:25:13 -0600 | asked a question | Object height detection (single camera) Dear all, Since I was not able to find an answer to this question in this forum, I decided to sign up and post it. Out of curiosity, I decided to do a small OpenCV project. The aim is to measure an objects height via a single camera. The camera may safely be assumed to be fixed, equally, the object's distance to the camera is known. Therefore, this equation should be solveable. AlgorithmCurrently my algorithm is as follows: (1) Calibrate Camera (2) Manually choose a point on the video stream which is on the ground (3) Detect object and upper object boundaries (y-coordinates) on the video stream (4) Calculate height: Difference between reference point (3) and upper object boundaries (4) is object's height. ProblemThis seems to work - however there is an error of 3 - 10 centimeters. The error seems to depend (a) on the quality of the calibration, (b) on the location of the object along the videos' x-Achsis (i.e. camera does not seem to be parallel to the ground) and (c) y position on the screen (the higher the object, the larger the error). As a result, I guess that I am doing something entirely wrong. To be more concrete, I will lay out the steps (1) to (4) in greater detail. (1) Camera CalibrationIs done via chessboard patterns which each have 26 mm of size. Basically I use an adaption of the Emgu CV (C# Bindings) examples and this link: http://dasl.mem.drexel.edu/~noahKuntz/openCVTut10.html (2) Manually choose a point that is on the groundFor reasons of convenience I simply click on the x,y-coordinate of the video stream, where the (image of the) ground intersects with the (image of the wall) within my room. Simple enough... (3) Detect upper object boundariesSimple feature detection which works well (proven by drawing circles around them). (4) Calculate heightHere it gets a bit tricky - though my approach is fairly simple. According to http://docs.opencv.org/modules/calib3d/doc/camera_calibration_and_3d_reconstruction.html (more specifically this formular http://docs.opencv.org/_images/math/69a88b04c61001bf4e198abae39569e8bc3e81c2.png) one should be able to compute real world Y-coordinates by calculating y = (v-c_y) * z/f_y. Using this formular I calculate y_upperBoundary and y_ground in real world coordinates (with respect to the cameras absolute position in real world coordinates, I assume). I provide the following inputs:
I assume the last step (calculating y_ground minus y_upperBoundary) is necessary, because ... (more) |