Practical Course: Computer Vision for Human-Computer Interaction

I contributed as a supervisor to the installments: SS2022, SS2024

This practical course explores the development of real-time, interactive computer vision systems for human–machine interaction. Students work individually or in small teams on subprojects within a common theme, with the option to propose their own ideas. The focus is on applying fundamental computer vision and machine learning methods to real-world scenarios, solving practical challenges, and testing systems in realistic environments. Through hands-on development, teamwork, and final presentations, participants gain technical skills, problem-solving experience, and the ability to communicate their work effectively (Website).

Topics and alumni:

• Anomaly Detection for the Singulation of Plastic Wastes in Polymer Recycling, Charlotte Goos, Aleksandr Eismont, Dmitrii Seletkov, 2022 (collaboration with Polysecure, ZEISS Innovation Hub@KIT)
• User friendly Visual in-Context Learning, Zhi Wang, Chen Zhang, Zhen Fan, 2024