Basic bangla sign language recognition and sentence building using Microsoft Kinect
This thesis report is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017.
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BRAC University
2018
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| Truy cập trực tuyến: | http://hdl.handle.net/10361/9490 |
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10361-94902022-01-26T10:04:54Z Basic bangla sign language recognition and sentence building using Microsoft Kinect Ahmed, Khan Rafin Mumu, Sabrin Momotaz Shuvra, Fatema Tuz Zohora Alam, Dr. Md. Ashraful Department of Computer Science and Engineering, BRAC University Sign language Microsoft kinect Spoken language Skeleton tracking Finger identification Kcurvature algorithm This thesis report is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017. Cataloged from PDF version of thesis report. Includes bibliographical references (pages 33-34). How do a deaf of mute people communicate with each other? Or, even bigger question, how do they make other people understand their messages? The answer is, Sign Language. It is not that easy, most people do not know sign languages. To improve that situation, there have been many researches going on to translate sign language into spoken language. The main purpose of our thesis was to build a system similar to that in Bangla language. When one signs a language, he mostly uses his hands and head. The facial impression is also important. In our system, we tracked the skeleton with the help of Kinect. The system performs hand segmentation, finger identification and the number of fingers the signer has used using K-curvature algorithm while making the gesture. To determine the movement, the information about the skeleton joints is checked from the data set for each gesture. Finally the system shows the output for which the conditions are matched. Thus, the system recognizes the sign language gestures. Keywords: Bangla Sign Language, Kinect, Skeleton Tracking, Finger Identification, Kcurvature algorithm. Khan Rafin Ahmed Sabrin Momotaz Mumu Fatema Tuz Zohora Shuvra B. Computer Science and Engineering 2018-02-18T04:22:40Z 2018-02-18T04:22:40Z 2017 2017 Thesis ID 12201111 ID 13101115 ID 13101114 http://hdl.handle.net/10361/9490 en BRAC University thesis reports 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. 34 pages application/pdf BRAC University |
| institution |
Brac University |
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Institutional Repository |
| language |
English |
| topic |
Sign language Microsoft kinect Spoken language Skeleton tracking Finger identification Kcurvature algorithm |
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Sign language Microsoft kinect Spoken language Skeleton tracking Finger identification Kcurvature algorithm Ahmed, Khan Rafin Mumu, Sabrin Momotaz Shuvra, Fatema Tuz Zohora Basic bangla sign language recognition and sentence building using Microsoft Kinect |
| description |
This thesis report is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017. |
| author2 |
Alam, Dr. Md. Ashraful |
| author_facet |
Alam, Dr. Md. Ashraful Ahmed, Khan Rafin Mumu, Sabrin Momotaz Shuvra, Fatema Tuz Zohora |
| format |
Thesis |
| author |
Ahmed, Khan Rafin Mumu, Sabrin Momotaz Shuvra, Fatema Tuz Zohora |
| author_sort |
Ahmed, Khan Rafin |
| title |
Basic bangla sign language recognition and sentence building using Microsoft Kinect |
| title_short |
Basic bangla sign language recognition and sentence building using Microsoft Kinect |
| title_full |
Basic bangla sign language recognition and sentence building using Microsoft Kinect |
| title_fullStr |
Basic bangla sign language recognition and sentence building using Microsoft Kinect |
| title_full_unstemmed |
Basic bangla sign language recognition and sentence building using Microsoft Kinect |
| title_sort |
basic bangla sign language recognition and sentence building using microsoft kinect |
| publisher |
BRAC University |
| publishDate |
2018 |
| url |
http://hdl.handle.net/10361/9490 |
| work_keys_str_mv |
AT ahmedkhanrafin basicbanglasignlanguagerecognitionandsentencebuildingusingmicrosoftkinect AT mumusabrinmomotaz basicbanglasignlanguagerecognitionandsentencebuildingusingmicrosoftkinect AT shuvrafatematuzzohora basicbanglasignlanguagerecognitionandsentencebuildingusingmicrosoftkinect |
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