问题描述
我在Python中使用OpenCV制作给定图像的特征描述符.为此，我正在使用 ORB 类.我不理解的是在使用 orb.detect 和 orb.compute 之后描述符数组包含的内容.方法.
I am using OpenCV in Python to make a feature descriptor of a give image. For that I am using ORB class.What I don't understand is what the descriptor array contains after using orb.detect and orb.compute methods.
下面是我的代码.
import cv2
from matplotlib import pyplot as plt
from sklearn.cluster import KMeans
img = cv2.imread('penguins.jpg',0)
# Initiate STAR detector
orb = cv2.ORB_create(nfeatures=1000)
# find the keypoints with ORB
kp = orb.detect(img,None)
# compute the descriptors with ORB
kp, des = orb.compute(img, kp)
# draw only keypoints location,not size and orientation
img2 = cv2.drawKeypoints(img,kp,des, color=(0,255,0), flags=0, )
plt.imshow(img2),plt.show()
print len(kp),len(des),len(des[1]), des[0]
最后一行的输出如下:
1000 1000 32 [221 65 79 237 6 2 111 112 116 194 243 70 83 99 177 113 118 228
62 238 233 181 37 76 244 171 230 128 45 178 96 49]
为什么 des 的每个元素的长度都是32?它代表什么?我知道它应该是与每个关键点相对应的描述符数组，但是这些数字究竟代表什么?
Why is the length of each element of des is 32? What does it represent? I know that it is supposed to be a descriptor array corresponding to each keypoint, but what exactly do those numbers represent?
我已经从链接.
推荐答案
每个ORB描述符的默认长度为32个字节.每个字节包含8个像素强度比较，如官方论文中所述: https://www.willowgarage.com/sites/default/files/orb_final.pdf
The default lenght of each ORB descriptor is 32 bytes. Each byte contains 8 pixel intensity comparisons as explained in the official paper: https://www.willowgarage.com/sites/default/files/orb_final.pdf
还要检查:OpenCV ORB描述符-如何精确地存储在一组字节中?
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