Evaluating modern computer vision techniques for Shape Language classification in meetings

Automatic understanding of meetings and negotiations

Bachelor Thesis (2025)
Author(s)

S.A. Stan (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

S. Tan – Mentor (TU Delft - Interactive Intelligence)

E. Salas Gironés – Mentor (TU Delft - Interactive Intelligence)

Maria Soledad Pera – Graduation committee member (TU Delft - Web Information Systems)

Faculty
Electrical Engineering, Mathematics and Computer Science
More Info
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Publication Year
2025
Language
English
Graduation Date
31-01-2025
Awarding Institution
Delft University of Technology
Project
CSE3000 Research Project
Programme
Computer Science and Engineering
Faculty
Electrical Engineering, Mathematics and Computer Science
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Abstract

Meetings represent a key component of collabora- tion in the workplace, serving purposes like brain- storming, discussion, and negotiation. Despite their importance, reaching a consensus among partici- pants can frequently be difficult because different people can leave the debate with different perspec- tives. In order to promote efficient communication and decision-making in organisational contexts, the use of the Shape Language is proposed. The Shape Language consists of shapes that people can use in meetings in order to represent abstract ideas, that would be difficult to represent by only words. In order to track how people interact with these ob- jects, computer vision tools can be used. This study aims to explore the current existing computer vi- sion tools for segmenting and classifying objects in meetings, aiming to find limitations in how well these models are able to recognize objects in the context of meetings and negotiations. Results of this study show that after fine-tuning four models on the custom dataset, they can recognize the three shapes provided as classes in most of the cases, but still make mistakes when assigning classes, or miss objects that they should classify all together, which show limitations of these modern tools.

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