This document provides an overview of computer vision and OpenCV. It discusses topics like optical character recognition, face detection, object recognition, shape capture and motion capture, self-driving cars, interactive games, industrial robots, and medical imaging. It then covers OpenCV concepts like image manipulation, transformations, edge detection, feature detection, histogram of oriented gradients, object tracking, and face detection. Code examples are provided for tasks like webcam sketching, contour detection, line detection, and facial merging.

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