This course focuses on the detection of features and boundaries in images. Feature and boundary detection is a critical preprocessing step for a variety of vision tasks including object detection, object recognition and metrology – the measurement of the physical dimensions and other properties of objects. The course presents a variety of methods for detecting features and boundaries and shows how features extracted from an image can be used to solve important vision tasks.
Features and Boundaries
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Features and Boundaries
This course is part of First Principles of Computer Vision Specialization
Instructor: Shree Nayar
4,705 already enrolled
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4.8
(50 reviews)
Beginner level
Recommended experience
25 hours to complete
3 weeks at 8 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Learn how to detect edges and corners in images.
Develop active contours (snakes) to find complex object boundaries.
Learn about the Hough Transform for finding simple parametric shapes in images.
Learn about image transformations and how to estimate the homography between two images.
Skills you'll gain
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Assessments
29 assignments
Taught in English
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This course is part of the First Principles of Computer Vision Specialization
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There are 6 modules in this course
What's included
7 readings2 discussion prompts8 plugins
What's included
2 readings6 assignments2 discussion prompts6 plugins
What's included
2 readings5 assignments2 discussion prompts5 plugins
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1 reading5 assignments2 discussion prompts5 plugins
What's included
1 reading6 assignments1 discussion prompt6 plugins
What's included
3 readings7 assignments2 discussion prompts7 plugins
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4.8
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TF
5
Reviewed on Jan 20, 2023
A little bit advanced, but the quality of the slides and presentations is superb.
KJ
5
Reviewed on Apr 27, 2022
Amazing course , Well explained and interesting assignments!!!
GP
5
Reviewed on Dec 20, 2023
Great overview for various topics. The highlight is the simple explanation for the SIFT algorithm operational concept imo.
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