![](/image/LogoVKU.png)
Vui lòng dùng định danh này để trích dẫn hoặc liên kết đến tài liệu này:
https://elib.vku.udn.vn/handle/123456789/960
Nhan đề: | Joint Spatial Geometric and Max-margin Classifier Constraints for Facial Expression Recognition Using Nonnegative Matrix Factorization |
Tác giả: | Mai, Lam Phan, Trong Thanh |
Từ khoá: | facial expressions nonnegative matrix factorization classification graph regularization spatial constraints |
Năm xuất bản: | 2019 |
Nhà xuất bản: | Da Nang Publishing House |
Tóm tắt: | In this paper, we propose a new approach to facial expression recognition based on the constrained non-negative matrix factorization algorithm. Our proposed method incorporated two tasks in an automatic expression analysis system: facial feature extraction and classification into expressions. To obtain local and geometric structure information in the data as much as possible, we unite max-margin classification into the constrained NMF optimization, resulting in a multiplicative updating algorithm is also proposed for solving optimization problem. Experimental results on JAFFE dataset demonstrate that the effectiveness of the proposed method with improved performances over the conventional dimension reduction methods. |
Mô tả: | Scientific Paper; Pages: 39-48 |
Định danh: | http://elib.vku.udn.vn/handle/123456789/960 |
Bộ sưu tập: | CITA 2019 |
Khi sử dụng các tài liệu trong Thư viện số phải tuân thủ Luật bản quyền.