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Facial Expression Recognition Using Signed Local Directional Pattern
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| dc.contributor.author | Das, Nayan | |
| dc.contributor.author | Hasan, Kazi Md. Jamil | |
| dc.date.accessioned | 2019-03-19T05:48:38Z | |
| dc.date.available | 2019-03-19T05:48:38Z | |
| dc.date.issued | 2018-04-22 | |
| dc.identifier.uri | http://dspace.ewubd.edu/handle/2525/3003 | |
| dc.description | This thesis submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering of East West University, Dhaka, Bangladesh. | en_US |
| dc.description.abstract | \Facial expression recognition has many implications nowadays. But due to lack of performance, human computer interaction is not a pleasurable experience yet. In this paper we have proposed a better version of the LDP (Local Directional Pattern). In the previous LDP calculation the Kirsch masks directional information were lost because of taking the absolute value. So we have proposed the sLDP approach. In this approach we are not going to lose the directional information of the Kirsch mask. Thats why we have taken the signed value for the LDP calculation. By applying sLDP we were able to get a signi cant improvement over the previous one for the 6-class expression of the cohn dataset. We also got a little bit of improvement of the 7-class expression as well. " | en_US |
| dc.language.iso | en_US | en_US |
| dc.publisher | East West University | en_US |
| dc.relation.ispartofseries | ;CSE00173 | |
| dc.subject | Facial Expression Recognition Using Signed Local Directional Pattern | en_US |
| dc.title | Facial Expression Recognition Using Signed Local Directional Pattern | en_US |
| dc.type | Thesis | en_US |
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Thesis 2018 [27]