OPENCV:Calibratecamera 2 重投影错误和自定义计算的不同意

I have a python script that uses the calibratecamera2 method to calibrate a camera from a few views of a checker board. After a successful calibration I go after all original points and do some plots and compute again the re-projection error. My surprise is that the reprojection error computed by opencv and mine are a bit different. I found it strange. Am I computing it in a wrong way?

obj_points = []# 3d point in real world space. List of arrays
img_points = []# 2d points in image plane. List of arrays

...

ret, camera_matrix, dist_coeffs, rvecs, tvecs = cv2.calibrateCamera(obj_points, img_points, (w, h), camera_matrix, dist_coeffs, rvecs, tvecs, calib_flags +cv2.CALIB_USE_INTRINSIC_GUESS, criteria)
print "Final reprojection error opencv: ", ret   #Compute mean of reprojection error
tot_mean_error=0
mean_error_image = 0
for i in xrange(len(obj_points)):
    reprojected_points, _ = cv2.projectPoints(obj_points[i], rvecs[i], tvecs[i], camera_matrix, dist_coeffs)
    reprojected_points=reprojected_points.reshape(-1,2)
    mean_error_image=np.sum(np.sum(np.abs(img_points[i]-reprojected_points)**2,axis=-1)**(1./2))/np.alen(reprojected_points)
    tot_mean_error +=mean_error_image

mean_error=tot_mean_error/len(obj_points)
print "Mean reprojection error: ", mean_error

最终重投影错误opencv:0.571030279037

#Compute mean of reprojection error
tot_error=0
total_points=0
for i in xrange(len(obj_points)):
    reprojected_points, _ = cv2.projectPoints(obj_points[i], rvecs[i], tvecs[i], camera_matrix, dist_coeffs)
    reprojected_points=reprojected_points.reshape(-1,2)
    tot_error+=np.sum(np.abs(img_points[i]-reprojected_points)**2)
    total_points+=len(obj_points[i])

mean_error=np.sqrt(tot_error/total_points)
print "Mean reprojection error: ", mean_error