Computer vision based employee activities analysis
This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2013.
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| Jezik: | English |
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Department of Computer Science and Engineering, BRAC University
2013
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| Online pristup: | http://hdl.handle.net/10361/2747 |
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10361-27472022-01-26T10:20:02Z Computer vision based employee activities analysis Hoque, Md. Rezwanul Karim, Nabil Tahmidul Rozario, Saikat Lawrence Md. Rumman Bin Ashraf Alom, Md. Zahangir Department of Computer Science and Engineering, BRAC University Computer science and engineering Real Time Face Recognition Principle Component Analysis Natural Language Processing Face recognition Haar Cascade Classifier This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2013. Cataloged from PDF version of thesis report. Includes bibliographical references (page 50). This paper presents an automated system for human face recognition in a real time background for a company to mark the attendance of their employees. So Smart Attendance using Real Time Face Recognition is a real world solution which comes with day to day activities of handling employees. The task is very difficult as the real time background subtraction in an image is still a challenge. To detect real time human face Haar cascade is used and a simple fast Principal Component Analysis is used to recognize the faces detected with a high accuracy rate. The matched face is then used to mark attendance of the employees. Our system generates how much time each employee spends at his workstation and provides update to the employer whenever he wants. This product gives much more solutions with accurate results in user interactive manner rather than existing attendance and leave management systems. Md. Rezwanul Hoque Nabil Tahmidul Karim Saikat Lawrence Rozario Ashraf, Md. Rumman Bin B. Computer Science and Engineering 2013-09-09T05:07:11Z 2013-09-09T05:07:11Z 2013 9/1/2013 Thesis ID 09201016 ID 09201020 ID 10101007 ID 10101028 http://hdl.handle.net/10361/2747 en BRAC University thesis 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. 51 pages application/pdf Department of Computer Science and Engineering, BRAC University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Computer science and engineering Real Time Face Recognition Principle Component Analysis Natural Language Processing Face recognition Haar Cascade Classifier |
| spellingShingle |
Computer science and engineering Real Time Face Recognition Principle Component Analysis Natural Language Processing Face recognition Haar Cascade Classifier Hoque, Md. Rezwanul Karim, Nabil Tahmidul Rozario, Saikat Lawrence Md. Rumman Bin Ashraf Computer vision based employee activities analysis |
| description |
This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2013. |
| author2 |
Alom, Md. Zahangir |
| author_facet |
Alom, Md. Zahangir Hoque, Md. Rezwanul Karim, Nabil Tahmidul Rozario, Saikat Lawrence Md. Rumman Bin Ashraf |
| format |
Thesis |
| author |
Hoque, Md. Rezwanul Karim, Nabil Tahmidul Rozario, Saikat Lawrence Md. Rumman Bin Ashraf |
| author_sort |
Hoque, Md. Rezwanul |
| title |
Computer vision based employee activities analysis |
| title_short |
Computer vision based employee activities analysis |
| title_full |
Computer vision based employee activities analysis |
| title_fullStr |
Computer vision based employee activities analysis |
| title_full_unstemmed |
Computer vision based employee activities analysis |
| title_sort |
computer vision based employee activities analysis |
| publisher |
Department of Computer Science and Engineering, BRAC University |
| publishDate |
2013 |
| url |
http://hdl.handle.net/10361/2747 |
| work_keys_str_mv |
AT hoquemdrezwanul computervisionbasedemployeeactivitiesanalysis AT karimnabiltahmidul computervisionbasedemployeeactivitiesanalysis AT rozariosaikatlawrence computervisionbasedemployeeactivitiesanalysis AT mdrummanbinashraf computervisionbasedemployeeactivitiesanalysis |
| _version_ |
1814309161661366272 |