Sinossi
Pose estimation is a difficult subject to solve. Existing position estimate approaches are general-purpose and do not function effectively on all yoga poses since a small number of yoga poses are sophisticated and not observed in everyday activities. A person can learn yoga in a variety of methods. Yoga can be learned at a yoga class or at home via self-teaching. With the help of books and videos, one can also read for herself. Many people prefer to study alone, yet it might be difficult for them to identify improper postures. Our project intends to replace traditional yoga learning techniques. The AI-Based Yoga Instructor project seeks to create an easy-to-use web interface to assist people in learning yoga in a simple and straightforward manner. In this paper, we provide improved pose comparison scoring metrics as well as enhancements to existing pose estimation algorithms to include yoga positions. The Media-Pipe pose estimation model is used in our study to recognize real-time human poses. Additionally, the detected pose is categorized using a heuristic angle-based approach to deliver relevant feedback to the user in order to help him or her improve their yoga poses.
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AI-BASED YOGA INSTRUCTOR
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LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6205491362
ISBN 13: 9786205491362
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AI-BASED YOGA INSTRUCTOR
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LAP LAMBERT Academic Publishing Aug 2022, 2022
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ISBN 13: 9786205491362
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Pose estimation is a difficult subject to solve. Existing position estimate approaches are general-purpose and do not function effectively on all yoga poses since a small number of yoga poses are sophisticated and not observed in everyday activities. A person can learn yoga in a variety of methods. Yoga can be learned at a yoga class or at home via self-teaching. With the help of books and videos, one can also read for herself. Many people prefer to study alone, yet it might be difficult for them to identify improper postures. Our project intends to replace traditional yoga learning techniques. The AI-Based Yoga Instructor project seeks to create an easy-to-use web interface to assist people in learning yoga in a simple and straightforward manner. In this paper, we provide improved pose comparison scoring metrics as well as enhancements to existing pose estimation algorithms to include yoga positions. The Media-Pipe pose estimation model is used in our study to recognize real-time human poses. Additionally, the detected pose is categorized using a heuristic angle-based approach to deliver relevant feedback to the user in order to help him or her improve their yoga poses. 68 pp. Englisch. Codice articolo 9786205491362
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AI-BASED YOGA INSTRUCTOR
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LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6205491362
ISBN 13: 9786205491362
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Condizione: New. Print on Demand. Codice articolo 400120272
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AI-BASED YOGA INSTRUCTOR
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LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6205491362
ISBN 13: 9786205491362
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ISBN 13: 9786205491362
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Kumar AtulEr. Pragati Singh and Er. Shashank Sahu are the graduates of Computer Science and Engineering of SRMCEM Lucknow. Dr. Atul is working as an Associate Professor in CSE Department.Pose estimation is a difficult subject to . Codice articolo 706504609
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AI-BASED YOGA INSTRUCTOR
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LAP LAMBERT Academic Publishing Aug 2022, 2022
ISBN 10: 6205491362
ISBN 13: 9786205491362
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Taschenbuch. Condizione: Neu. Neuware -Pose estimation is a difficult subject to solve. Existing position estimate approaches are general-purpose and do not function effectively on all yoga poses since a small number of yoga poses are sophisticated and not observed in everyday activities. A person can learn yoga in a variety of methods. Yoga can be learned at a yoga class or at home via self-teaching. With the help of books and videos, one can also read for herself. Many people prefer to study alone, yet it might be difficult for them to identify improper postures. Our project intends to replace traditional yoga learning techniques. The AI-Based Yoga Instructor project seeks to create an easy-to-use web interface to assist people in learning yoga in a simple and straightforward manner. In this paper, we provide improved pose comparison scoring metrics as well as enhancements to existing pose estimation algorithms to include yoga positions. The Media-Pipe pose estimation model is used in our study to recognize real-time human poses. Additionally, the detected pose is categorized using a heuristic angle-based approach to deliver relevant feedback to the user in order to help him or her improve their yoga poses.Books on Demand GmbH, Überseering 33, 22297 Hamburg 68 pp. Englisch. Codice articolo 9786205491362
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AI-BASED YOGA INSTRUCTOR
Editore:
LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6205491362
ISBN 13: 9786205491362
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Da: AHA-BUCH GmbH, Einbeck, Germania
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Pose estimation is a difficult subject to solve. Existing position estimate approaches are general-purpose and do not function effectively on all yoga poses since a small number of yoga poses are sophisticated and not observed in everyday activities. A person can learn yoga in a variety of methods. Yoga can be learned at a yoga class or at home via self-teaching. With the help of books and videos, one can also read for herself. Many people prefer to study alone, yet it might be difficult for them to identify improper postures. Our project intends to replace traditional yoga learning techniques. The AI-Based Yoga Instructor project seeks to create an easy-to-use web interface to assist people in learning yoga in a simple and straightforward manner. In this paper, we provide improved pose comparison scoring metrics as well as enhancements to existing pose estimation algorithms to include yoga positions. The Media-Pipe pose estimation model is used in our study to recognize real-time human poses. Additionally, the detected pose is categorized using a heuristic angle-based approach to deliver relevant feedback to the user in order to help him or her improve their yoga poses. Codice articolo 9786205491362
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ISBN 10: 6205491362
ISBN 13: 9786205491362
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Taschenbuch. Condizione: Neu. AI-BASED YOGA INSTRUCTOR | Atul Kumar (u. a.) | Taschenbuch | Englisch | 2022 | LAP LAMBERT Academic Publishing | EAN 9786205491362 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Codice articolo 124654053
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