廣宣學堂機器視覺系列: 機器視覺初探

1. & &
Jerry

2. •
• ”
•
• Founder
•
• MIT edX/MandarinX
•
• https://www.ap-mic.com
• http://dataology.blogspot.tw
• https://www.linkedin.com/in/jerry2012/
(Jerry)
dsjerry2017@gmail.com 2

3. 3

4. VM

5. • vmware-tools-distrib
• sudo ./vmware-install.pl

6. Jupyter Notebook
• sudo pip3 install jupyter
• sudo apt-get install python3-matplotlib

8. (Computer Vision)
•
Make computers understand images and video.

9. -

10. -

11. -
U

12. • Safety
• Health
• Security
• Comfort
• Fun
• Access
• …….

13. • 1960
• 1970
• 1990 C 3
• 2000
• 2030

15. -OCR
(OCR, Optical Character Recognition)

16. - Face detection

17. - Smile detection

18. - Object recognition

19. - Vision-based biometrics

20. - Login without a password

21. - Shape Capture & Motion Capture

22. - Self-Driving Cars
Mobileye
– Vision systems currently in high-end BMW, GM, Volvo, Tesla

23. - Interactive Games: Kinect

24. - Industrial robots

25. - Medical imaging

28. • Viewpoint Variations

29. image credit: J. Koenderink

30. a

31. “
• Occlusion
image credit: Magritte, 1957

32. • Clutter

34. 3D
• Optical Illusions

35. OpenCV?

36. OpenCV
• OpenCV 2000 17
• Intel
• *
•
•
• S
• OpenCV C++
• ' Python, Java, Matlab, C#, Ruby
• OpenCV
• Windows Mac OS Linux Android

37. Python + OpenCV
• P OpenCV
• (CV)
• OpenCV
• Python Numpy Scikit-learn
• BSD S
•
• Windows Mac Linux
• ' CUDA GPU
• Python

38. ?

40. •
Title

41. RGB

43. 3
•
•
•

44. 3

45. 3

46. RGB & HSV
• RGB U RGB color model
Red Green Blue
a V
• HSL Hue, Saturation,
Lightness HSL
• H
• S
0-100%
• V 0-100%

47. 3
OpenCV stores color in the BGR format.

48. 3
RGB 3

49. 3 (RGB)
BGR

50. • cv2.calcHist(images, channels, mask, histSize, ranges[, hist[,
accumulate]])
• images :
• Channels [0] [0],[1],[2]( )
• Mask None
• histSize 3 bins [256]
• Ranges [0, 256]

51. ravel() array
calcHist
enumerate col

53. OpenCV
• 3 (Square)
np.zeros array

54. OpenCV
• (Line)
Cv2.line ( )

55. OpenCV
• 3 (Rectangle)

56. OpenCV
• (Circle)

57. OpenCV
• (Polygon)

58. Image Manipulations

59. (Transformations)
• (Transformations) : (Affine) (Non-Affine)
• (Affine)
• (Non-Affine) Scaling
Rotation
Translation

60. (Translations)
Tx 311.25
Ty 207.5
Tx
Ty

61. (Rotations)
Cos θ -Sin θ
Sin θ Cos θ
θ ”
θ
*X Y

62. (Rotations)-Transpose

63. c (Horizontal Flip)
1 c
0
-1 c

64. *(Scaling) (Resizing) (Interpolations)
* 3/4
cv2.INTER_AREA
* cv2.INTER_CUBIC
resize cv2.INTER_LINEAR
None Fx Fy *

65. (Image Pyramids)

66. (Cropping)

67. r (Added) & (Subtracted)
Mr

68. (Bitwise) & “ (Masking)

69. Bitwise Operations and Masking
3

70. (Convolutions) & U (Blurring)

71. (Sharpening)

72. Thresholding, Binarization & Adaptive Thresholding
127 0 255
127 255 127 0
127 127 255
127 0 127
127 127 0

73. Thresholding, Binarization & Adaptive Thresholding
127 0 255
U o
Adaptive Threshold
y

74. (Dilation) & (Erosion)
Kernel

75. u(Edge Detection)
Sobel
## threshold1 threshold2
R 2
1
1 2 e
#intensities 60 R
120
Canny u R
R

76. u(Edge Detection)

77. (Perspective Transform)
4
A4 1 1.41 a

78. (Perspective Transform)

79. Webcam Sketch
Guassian Blurs
cap VideoCapture
frame

80. Image Segmentation

81. (Contours)
3

82. (Sorting Contours)
Canny

83. Line Detection - Using Hough Lines
Canny
1 rho HoughLines
np.pi / 180 1
240

84. Line Detection - Using Hough Lines(2)

85. Blob Detection
u
u
u blob

86. Counting Circles and Ellipses(1)
u
u
blob

87. Identifiy Contours by Shape(2)
y
y
y
y
y
u
u

88. u
Object Detection

89. (Waldo)
Martin Handford
n
——
D

90. Finding Waldo

91. Finding Corners
cornerHarris float32

92. Feature Detection- SIFT
SIFT Feature Detector
u

93. Feature Detection- SURF
SURF Feature Detector

94. Feature Detection- FAST
FAST u #fast = cv2.FastFeatureDetector

95. Feature Detection-
Oriented FAST and Rotated BRIEF (ORB)
ORB

96. Histogram of Oriented Gradients(1)
h x w( )
h x w
OpenCV HOG
winSize
hog_feats numpy

97. Histogram of Oriented Gradients(2)
# R
Matplotlib HOG
360 / nbins *3

98. SIFT Webcam Demo
Run feature_homography.py

99. u
Face Detection

100. u
OpenCV CascadeClassifier
XML-
u ROI
u face_classifier
faces

101. u

102. Webcam Demo(1)

103. Merging Faces(1)
U

104. Merging Faces(2)
x y

105. Merging Faces(3)

106. Merging Faces(4)
t e

107. Merging Faces(5)

108. Merging Faces(6)

109. Merging Faces(7)

110. Motion Analysis- Yawn Detector and Counting
• OpenCV u
•

111. Yawn Detector and Counting(1)

112. Yawn Detector and Counting(2)

113. Yawn Detector and Counting(3)

114. • OpenCV iPhone X Face ID
• c
•
• 2D3 3D
• iPhone X (Infrared)

115. - U
numpy
numpy
U

116. - Webcam Demo(1)

117. - Webcam Demo(2)
U u
c

118. • face_recognition
examples/facerec_
from_webcam.py

119. Object Tracking

120. (Object Tracking)
• u
• u Video
Tracking 3
• (Optical Flow)

121. (Object Tracking)
u
Lucas kanade

122. (Object Tracking)
1

123. dsjerry2017@gmail.com
jerry@mail.ntust.edu.tw
dsjerry2017@gmail.com 123

124. • opencv examples/lk_homography.py
• opencv examples/python3 lk_track.py