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Biometrics
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Classroom Contents
Introduction to Computer Vision - Lecture 1
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- 1 What is computer vision?
- 2 Visual Perception
- 3 Vision vs. Computer Vision?
- 4 Vision and Image Understanding
- 5 Goal of Computer Vision? • To bridge the gap between
- 6 What is a (digital) Image?
- 7 Image Types: (Gray)Scalar and Binary
- 8 Image Type: RGB (red, green, blue)
- 9 Color
- 10 Retina of Human Eye
- 11 Recent advancement
- 12 What changed?
- 13 Investment in computer vision
- 14 CVPR conference ranking (Engineering)
- 15 CVPR attendance
- 16 Police chase
- 17 Retail - Amazon Go
- 18 Retail - Clothing
- 19 Self-driving - Waymo
- 20 Autopilot - Tesla
- 21 Object Recognition
- 22 Object localization
- 23 Human Detection
- 24 Semantic Segmentation: Results
- 25 Semantic part labeling
- 26 Face Recognition
- 27 Open Universe Face Identification
- 28 Facial expression
- 29 Fatigue detection
- 30 Lip-reading
- 31 High Density Crowded Scenes
- 32 Counting
- 33 Visual Business Recognition
- 34 Biometrics
- 35 Smile detection
- 36 Sequences of Images
- 37 Action recognition - UCF101
- 38 Action detection
- 39 Video segmentation
- 40 Cross-view action synthesis
- 41 Detection in aerial videos
- 42 (Object) Tracking
- 43 Video Surveillance and Monitoring
- 44 Naive approach: Template Matching
- 45 Computer vs. Human Vision?
