卢卡斯-卡纳德失去跟踪点OpemCv Python

Question

我是Python和OpenCV的新手。我使用了lucas-kanade示例，您可以在下面看到。现在，我为我的Raspberry PI box制作了一个foto，其中的代码检测到5个点(参见图1) Lucas-Kanade-tracked-Points。在第二张图片中，我在盒子前面从左到右稍微移动了一张纸。在那里，我看到，我的5个跟踪点可以通过这张纸移动。这5点现在附加在本文的长边(参见图2) moved tracked points。那件事怎么可能？为什么我可以移动这些点？在我看来，当我将这张纸移到它们上面时，它们必须丢失。有人能帮帮我吗？

致以最好的问候，汉兹

import numpy as np
import cv2
cap = cv2.VideoCapture(0)
# params for ShiTomasi corner detection
feature_params = dict( maxCorners = 100,
                       qualityLevel = 0.3,
                       minDistance = 7,
                       blockSize = 7 )
# Parameters for lucas kanade optical flow
lk_params = dict( winSize  = (15,15),
                  maxLevel = 2,
                  criteria = (cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 0.03))
# Create some random colors
color = np.random.randint(0,255,(100,3))
# Take first frame and find corners in it
ret, old_frame = cap.read()
old_gray = cv2.cvtColor(old_frame, cv2.COLOR_BGR2GRAY)
p0 = cv2.goodFeaturesToTrack(old_gray, mask = None, **feature_params)
# Create a mask image for drawing purposes
mask = np.zeros_like(old_frame)
while(1):
    ret,frame = cap.read()
    frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    # calculate optical flow
    p1, st, err = cv2.calcOpticalFlowPyrLK(old_gray, frame_gray, p0, None, **lk_params)
    # Select good points
    good_new = p1[st==1]
    good_old = p0[st==1]
    # draw the tracks
    for i,(new,old) in enumerate(zip(good_new,good_old)):
        a,b = new.ravel()
        c,d = old.ravel()
        mask = cv2.line(mask, (a,b),(c,d), color[i].tolist(), 2)
        frame = cv2.circle(frame,(a,b),5,color[i].tolist(),-1)
    img = cv2.add(frame,mask)
    cv2.imshow('frame',img)
    k = cv2.waitKey(30) & 0xff
    if k == 27:
        break
    # Now update the previous frame and previous points
    old_gray = frame_gray.copy()
    p0 = good_new.reshape(-1,1,2)
cv2.destroyAllWindows()
cap.release()

Answer 1

我找到了一个解决方案。我必须用下面的点检查前面的点，如本例所示，可以在这里找到https://github.com/opencv/opencv/blob/master/samples/python/lk_homography.py

下面是相关的代码行：

def checkedTrace(img0, img1, p0, back_threshold = 1.0):
    p1, _st, _err = cv.calcOpticalFlowPyrLK(img0, img1, p0, None, **lk_params)
    p0r, _st, _err = cv.calcOpticalFlowPyrLK(img1, img0, p1, None, **lk_params)
    d = abs(p0-p0r).reshape(-1, 2).max(-1)
    status = d < back_threshold
return p1, status