Блог

Я пытаюсь восстановить 3D-траекторию теннисного мяча по видео с использованием (x, y, size) мяча с плоскости изображения, которое я получил с помощью OpenCV.

Ниже x,y, size приведены из каждого кадра.
x,y координаты представлены в следующем формате

значения в sizes радиусе * 2 от кадров
time.time() когда были получены значения

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Используя эту бумагу в качестве руководства, я получил предположительно откалиброванную камеру
используя 6 точек из одного из кадров, ниже приведен код для этого

 # Camera Calibration
import numpy as np

# 4 x,y coordinates of court corners and 2 points under the net
imgPts = [[577, 303], [1333, 303], [495, 517], [1422, 517], [366, 857], [1562, 857]]

# Assuming the top left corner is origin
# Moving to the right is  x, and down is  y, z is 0 
objPts = [[0, 0, 0], [10.97, 0, 0], [0, 11.8, 0], [10.97, 11.8, 0], [0, 23.77, 0], [10.97, 23.77, 0]]

objPts = np.array(objPts)
objPts = objPts.astype('float32')
imgPts = np.array(imgPts)
imgPts = imgPts.astype('float32')

w = frame.shape[1]
h = frame.shape[0]
size = (w,h)

camera_matrix = cv2.initCameraMatrix2D([objPts],[imgPts], size)

rms, camera_matrix, dist_coefs, rvecs, tvecs = cv2.calibrateCamera([objPts], [imgPts], size, None, None)
 

и нашел омографию, используя следующую функцию

 def warpImage(img, points, w, h, pad=20):
  pts1 = np.float32(points)
  pts2 = np.float32([[0, 0], [w, 0], [0, h], [w, h]])
  matrix = cv2.getPerspectiveTransform(pts1, pts2)
  imgWarp = cv2.warpPerspective(img, matrix, (w, h))
  imgWarp = imgWarp[pad:imgWarp.shape[0]-pad, pad:imgWarp.shape[1]-pad]

  return matrix, imgWarp

angles = np.array([[577 , 303], [1333, 303], [366, 857], [1565 ,857]]).reshape(4,1,2)

courtW = 1097 # court width  = 10.97 meters in cm
courtH = 2377 # court length = 23.77 meters in cv


homMat, img = warpImage(frame, angles, courtW, courtH, pad=0)
 

Но теперь я не знаю, что делать дальше, пожалуйста, помогите, если есть решение!