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I tried H1 and H2 instead of Q. But it shows the same error.

Now am doing conversion of 2D image to 3D image. So for that I am using the function reprojectImageTo3D(imgDisparity8U, xyz, Q, true); But I got an error like this.

Assertion failed (Q.size() == Size(4,4)) in reprojectImageTo3D, file /home/arya/stuff/opencv/opencv-2.4.7/modules/calib3d/src/calibration.cpp, line 2823

Could you tell me what is xyz and Q? And what are the values given to these variables?

Now I am doing conversion of 2D images to 3D images. For that am using following steps.

(1). Input 2 images. (2). Detect keypoints using SIFT. (3). Extract Descriptors. (4). Compare and match descriptors. (5). find fundamental mat (findFundamentalMat()) from these pairs. (6). stereoRectifyUncalibrated(). (7). reprojectImageTo3D().

Now I want to know that what is this xyz and Q in reprojectImageTo3D? And what are the values given to xyz and to Q?

reprojectImageTo3D(imgDisparity8U, xyz, Q, true);

Because I got an error like this:

OpenCV Error: Assertion failed (Q.size() == Size(4,4)) in reprojectImageTo3D, file /home/arya/stuff/opencv/opencv-2.4.7/modules/calib3d/src/calibration.cpp, line 2823

ok.Thank you for your reply..

I already set this minimum face size and maximum face size. double min_face_size=30; double max_face_size=400; these values are used at the time of detection. But I don't know where I set minimum face size at the time of recognition.

So what I do to overcome this? Do you have any suggestions or solution?

But in my case when a person nearer to camera it identify as known but when distance increases the same person identify as unknown. Could you tell me why?

Is it possible to achieve some sort of distance using SURF features?

i don't have any code