使用扭曲的透视图像

Question

简介：根据我的理解，给定移动物体的同一场景的2张图像，我可以在每个像素上制作一个均值以“移除”移动的物体（它会有重影效果，但如果我将重复几个图像，它会很好。）

然而，如果我有不同的场景，这根本不起作用，所以我想将我的所有图像移动到同一场景（扭曲透视图），然后执行上面的建议。

我想从我拥有的电影帧中删除移动物体。为此，我找到了两个图像之间的匹配关键点，使用RANSAC去除异常值，并将图像A的透视图扭曲到图像B的透视图以获得扭曲的图像。

现在我希望扭曲的图像与src,dst图像的大小相同，但这不是我得到的：

最终我希望从几个帧中获得一个完整的扭曲图像，并使用它来移除从一帧到另一帧移动的对象。

1. 如何以完整尺寸创建扭曲图像？
2. 如何找到我想表示值​​的相应像素，以便删除移动物体？

# find key points + features of a given image
def get_keyPoints_and_features(img):
    descriptor = cv2.xfeatures2d.SIFT_create()
    kps, features = descriptor.detectAndCompute(img, None)
    kps = np.float32([kp.pt for kp in kps])
    return kps, features

# match key points of 2 images 
def match_key_points(a, b, ratio = 0.75):
    # unpack 
    kpsA, featuresA = a
    kpsB, featuresB = b

    matcher = cv2.DescriptorMatcher_create("BruteForce")
    rawMatches = matcher.knnMatch(featuresA, featuresB, 2)
    matches = []

    # remove outliers using RANSAC
    for m in rawMatches:
        if len(m) == 2 and m[0].distance < m[1].distance * ratio:
            matches.append((m[0].trainIdx, m[0].queryIdx))

    # must have more than 4 matches
    # the more matches we have, the more noise robust it will be
    assert(len(matches) > 4)
    ptsA = np.float32([kpsA[i] for (_, i) in matches])
    ptsB = np.float32([kpsB[i] for (i, _) in matches])
    (H, status) = cv2.findHomography(ptsA, ptsB, method = cv2.RANSAC, 
                                        ransacReprojThreshold = 0.4)
    return matches, H

# warp src image to have perspective like dst image using the 
# homogrpahy between both images
def warp_perspective(src, dst):
    # read images
    a,b = cv2.imread(src), cv2.imread(dst)

    # generate key points and features
    kps_and_features_a = get_keyPoints_and_features(a)
    kps_and_features_b = get_keyPoints_and_features(b)

    # get homography
    _, H = match_key_points(kps_and_features_a, kps_and_features_b)

    warped = cv2.warpPerspective(a, H, (a.shape[1], a.shape[0]))
    inv_warped = cv2.warpPerspective(warped, inv(H), (a.shape[1], a.shape[0]))

    cv2.imshow("a", a)
    cv2.imshow("b", b)
    cv2.imshow("warped", warped)
    cv2.imshow("inv_warped", inv_warped)
    cv2.moveWindow("a",0,0)
    cv2.moveWindow("b",0,370)
    cv2.moveWindow("warped",600,0)
    cv2.moveWindow("inv_warped",600,370)
    cv2.waitKey(0)
    cv2.destroyAllWindows()

def main():
    # get images
    path = r'...'
    images = [os.path.join(path, file) for file in os.listdir(path)]
    warp_perspective(images[0], images[1])

main()