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Fitness Guardian: Human Body Pose Recognition Application for Fitness Training

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dc.contributor.author Hapangama, Tanuk
dc.date.accessioned 2025-06-16T09:51:23Z
dc.date.available 2025-06-16T09:51:23Z
dc.date.issued 2024
dc.identifier.citation Hapangama, Tanuk (2024) Fitness Guardian: Human Body Pose Recognition Application for Fitness Training. BSc. Dissertation, Informatics Institute of Technology en_US
dc.identifier.issn 20200815
dc.identifier.uri http://dlib.iit.ac.lk/xmlui/handle/123456789/2596
dc.description.abstract The goal of this project Fitness Guardian is to create a tailored fitness trainer application that will improve users' training experiences by utilizing human body pose recognition models. The application analyzes users' workout form in real-time and offers feedback for better performance and injury prevention using computer vision and machine learning algorithms. The study examines the development of fitness trainer systems and emphasizes the need for precise body pose recognition and feedback. Maintaining good form during workouts is one of the main issues in fitness training, and this project aims to address it by integrating cutting-edge technology. The author suggests an approach where a pre-existing pose estimation model and a trained form prediction model are used in sync to provide real time feedback. en_US
dc.language.iso en en_US
dc.subject Pose Estimation en_US
dc.subject Workout en_US
dc.subject Personal Trainer en_US
dc.title Fitness Guardian: Human Body Pose Recognition Application for Fitness Training en_US
dc.type Thesis en_US


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