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.
Overview
Syllabus
What is computer vision?
Visual Perception
Vision vs. Computer Vision?
Vision and Image Understanding
Goal of Computer Vision? • To bridge the gap between
What is a (digital) Image?
Image Types: (Gray)Scalar and Binary
Image Type: RGB (red, green, blue)
Color
Retina of Human Eye
Recent advancement
What changed?
Investment in computer vision
CVPR conference ranking (Engineering)
CVPR attendance
Police chase
Retail - Amazon Go
Retail - Clothing
Self-driving - Waymo
Autopilot - Tesla
Object Recognition
Object localization
Human Detection
Semantic Segmentation: Results
Semantic part labeling
Face Recognition
Open Universe Face Identification
Facial expression
Fatigue detection
Lip-reading
High Density Crowded Scenes
Counting
Visual Business Recognition
Biometrics
Smile detection
Sequences of Images
Action recognition - UCF101
Action detection
Video segmentation
Cross-view action synthesis
Detection in aerial videos
(Object) Tracking
Video Surveillance and Monitoring
Naive approach: Template Matching
Computer vs. Human Vision?
Taught by
UCF CRCV
