dc.contributor.advisor | Ashraf, Faisal Bin | |
dc.contributor.author | Islam, Abidul | |
dc.contributor.author | Sadman, Zarif | |
dc.contributor.author | Imran, Shah | |
dc.contributor.author | Islam, Sazzadul | |
dc.date.accessioned | 2023-03-22T06:17:35Z | |
dc.date.available | 2023-03-22T06:17:35Z | |
dc.date.copyright | 2022 | |
dc.date.issued | 2022-05 | |
dc.identifier.other | ID 18301144 | |
dc.identifier.other | ID 18301008 | |
dc.identifier.other | ID 18326032 | |
dc.identifier.other | ID 18301162 | |
dc.identifier.uri | http://hdl.handle.net/10361/18002 | |
dc.description | This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022. | en_US |
dc.description | Cataloged from PDF version of thesis. | |
dc.description | Includes bibliographical references (pages 36-37). | |
dc.description.abstract | Yoga is one of the best activities from home to preserve our physical condition in
the present epidemic. Yoga, on the other hand, is all about performing the 82
Yoga Asanas correctly over the course of six classes. Regrettably, not everyone have
the knowledge or can perform yoga accurately. So to do yoga poses correctly we
will have to find a yoga instructor, but it can be very hard and expensive to find
yoga instructors considering all possible general situation and status. Using Deep
Learning(DL), picture categorization and various machine learning approaches, we
attempted to build a system or a model that will operate as a self-instructor of
Yoga for the user to classify different poses of yoga to distinguish accurate pose
in our thesis. It will assist the user in performing Yoga correctly by recognizing
errors in their Yoga Asanas. In a nutshell, this section will cover several posture
estimation, key point detection, and pose categorization techniques. Moreover, we
tried ensemble modeling as a booster to improve the pose prediction accuracy as
much as possible. | en_US |
dc.description.statementofresponsibility | Abidul Islam | |
dc.description.statementofresponsibility | Zarif Sadman | |
dc.description.statementofresponsibility | Shah Imran | |
dc.description.statementofresponsibility | Sazzadul Islam | |
dc.format.extent | 37 pages | |
dc.language.iso | en | en_US |
dc.publisher | Brac University | en_US |
dc.rights | Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. | |
dc.subject | Yoga posture | en_US |
dc.subject | Deep learning | en_US |
dc.subject | Learning theory | en_US |
dc.subject | Artificial intelligence (AI) | en_US |
dc.subject.lcsh | Machine learning | |
dc.subject.lcsh | Cognitive learning theory | |
dc.title | Yoga posture recognition using the deep learning process | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Department of Computer Science and Engineering, Brac University | |
dc.description.degree | B. Computer Science | |