Teaching Computer Vision the Interactive Way
Organizing Computer Vision Competition
In 2019, I had the opportunity to design and teach a comprehensive course titled Practical Digital Image Processing at Ain Shams University. The course aimed to provide students with hands-on experience in fundamental techniques and applications of computer vision.
To motivate students and foster innovation, I co-organized the Ain Shams University Computer Vision Competition (CVC), which allowed participants to apply their knowledge by developing creative solutions to practical problems in computer vision. The competition showcased advancements in computer vision applications and served as a platform for students to explore cutting-edge research and applications.
CVC was a particularly successful event that drew extensive participation and innovation. Organized by myself, Mohamed Ashraf, and Dr. Mahmoud Khalil, the competition aimed to gather and highlight the latest computer vision advances, offering a collaborative space for students and researchers to apply computer vision methods to real-life problems.
Competition Highlights
During both competitions, students presented a wide range of innovative projects. In the 2019 edition, the Top 20 Projects were showcased, demonstrating the participants’ creativity and technical skill. These projects explored various applications of computer vision, highlighting the students’ ability to translate theoretical knowledge into practical solutions.
This teaching and competition experience emphasized the importance of applying theoretical knowledge to solve real-world problems, encouraging students to push the boundaries of computer vision and machine learning applications.
Course Content
The course covered several essential topics in digital image processing and computer vision, such as:
- Introduction to Practical Image Processing
- Transformation and Edge Detection
- Hough Transform and Corner Detection
- Feature Descriptors and Feature Matching
- Stereo Images, Optical Flow, and Machine Learning
This course not only enhanced students’ knowledge of image processing fundamentals but also prepared them for practical applications by exposing them to various techniques used in real-world scenarios.