Goal of Computer Vision? • To bridge the gap between
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What is a (digital) Image?
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Image Types: (Gray)Scalar and Binary
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Image Type: RGB (red, green, blue)
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Color
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Retina of Human Eye
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Recent advancement
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What changed?
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Investment in computer vision
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CVPR conference ranking (Engineering)
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CVPR attendance
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Police chase
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Retail - Amazon Go
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Retail - Clothing
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Self-driving - Waymo
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Autopilot - Tesla
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Object Recognition
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Object localization
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Human Detection
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Semantic Segmentation: Results
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Semantic part labeling
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Face Recognition
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Open Universe Face Identification
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Facial expression
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Fatigue detection
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Lip-reading
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High Density Crowded Scenes
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Counting
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Visual Business Recognition
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Biometrics
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Smile detection
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Sequences of Images
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Action recognition - UCF101
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Action detection
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Video segmentation
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Cross-view action synthesis
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Detection in aerial videos
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(Object) Tracking
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Video Surveillance and Monitoring
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Naive approach: Template Matching
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Computer vs. Human Vision?
Description:
Explore the fundamentals of computer vision in this comprehensive lecture from the University of Central Florida's CAP5415 course. Delve into the core concepts of visual perception, digital image types, and the distinctions between human and computer vision. Discover recent advancements in the field, including applications in retail, self-driving cars, object recognition, face detection, and action recognition. Examine the growing importance of computer vision in various industries and its impact on technology. Learn about key techniques such as semantic segmentation, object tracking, and video surveillance. Gain insights into the challenges and opportunities in bridging the gap between human and computer visual understanding.