請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/56787完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 吳家麟 | |
| dc.contributor.author | Cheng-Yang Wu | en |
| dc.contributor.author | 吳政陽 | zh_TW |
| dc.date.accessioned | 2021-06-16T05:48:27Z | - |
| dc.date.available | 2015-08-16 | |
| dc.date.copyright | 2014-08-16 | |
| dc.date.issued | 2014 | |
| dc.date.submitted | 2014-08-09 | |
| dc.identifier.citation | [1] C. Anderson, P. Burt, and G. Van Der Wal. Change detection and tracking using
pyramid transform techniques. In 1985 Cambridge Symposium, pages 72–78. International Society for Optics and Photonics, 1985. [2] A. Asthana, S. Zafeiriou, S. Cheng, and M. Pantic. Robust discriminative response map fitting with constrained local models. In Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on, pages 3444–3451. IEEE, 2013. [3] P. N. Belhumeur, J. P. Hespanha, and D. Kriegman. Eigenfaces vs. fisherfaces: Recognition using class specific linear projection. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 19(7):711–720, 1997. [4] V. Bettadapura. Face expression recognition and analysis: the state of the art. arXiv preprint arXiv:1203.6722, 2012. [5] G. de Haan and V. Jeanne. Robust pulse rate from chrominance-based rppg. IEEE transactions on bio-medical engineering, 60(10):2878, 2013. [6] H. Gunes and B. Schuller. Categorical and dimensional affect analysis in continuous input: Current trends and future directions. Image and Vision Computing, 31(2):120–136, 2013. 18 [7] S. Jarlier, D. Grandjean, S. Delplanque, K. N’diaye, I. Cayeux, M. I. Velazco, D. Sander, P. Vuilleumier, and K. R. Scherer. Thermal analysis of facial muscles contractions. Affective Computing, IEEE Transactions on, 2(1):2–9, 2011. [8] L. Kong, Y. Zhao, L. Dong, Y. Jian, X. Jin, B. Li, Y. Feng, M. Liu, X. Liu, and H. Wu. Non-contact detection of oxygen saturation based on visible light imaging device using ambient light. Optics express, 21(15):17464–17471, 2013. [9] K. P. Murphy. Machine learning: a probabilistic perspective. 2012. [10] B. R. Nhan and T. Chau. Classifying affective states using thermal infrared imaging of the human face. Biomedical Engineering, IEEE Transactions on, 57(4):979–987, 2010. [11] M.-Z. Poh, D. J. McDuff, and R. W. Picard. Non-contact, automated cardiac pulse measurements using video imaging and blind source separation. Optics Express, 18(10):10762–10774, 2010. [12] M.-Z. Poh, D. J. McDuff, and R. W. Picard. Advancements in noncontact, multiparameter physiological measurements using a webcam. Biomedical Engineering, IEEE Transactions on, 58(1):7–11, 2011. [13] M. Soleymani, J. Lichtenauer, T. Pun, and M. Pantic. A multimodal database for affect recognition and implicit tagging. Affective Computing, IEEE Transactions on, 3(1):42–55, 2012. [14] N. Sun, M. Garbey, A. Merla, and I. Pavlidis. Imaging the cardiovascular pulse. In Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on, volume 2, pages 416–421. IEEE, 2005. [15] L. Tarassenko, M. Villarroel, A. Guazzi, J. Jorge, D. Clifton, and C. Pugh. Noncontact video-based vital sign monitoring using ambient light and auto-regressive models. Physiological measurement, 35(5):807, 2014. [16] M. Turk and A. Pentland. Eigenfaces for recognition. Journal of cognitive neuroscience, 3(1):71–86, 1991. [17] W. Verkruysse, L. O. Svaasand, and J. S. Nelson. Remote plethysmographic imaging using ambient light. Optics Express, 16(26):21434–21445, 2008. [18] G. Welch and G. Bishop. An introduction to the kalman filter, 1995. [19] H.-Y. Wu, M. Rubinstein, E. Shih, J. Guttag, F. Durand, and W. T. Freeman. Eulerian video magnification for revealing subtle changes in the world. ACM Transactions on Graphics (Proc. SIGGRAPH 2012), 31(4), 2012. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/56787 | - |
| dc.description.abstract | 本論文提出了一利用臉部膚色之時空變異特性的情緒分類方式。過去使用生理訊號分類情緒的方法往往會受到訊號取得不易的限制，或者是用以取得訊號的裝置昂貴，從而使此無法實用。
我們在本論文中利用了遠距生理訊號量測的原理，透過一空間-時間濾波的方式，將臉部之生理訊號，從由一般攝影機所拍攝的影片中擷取出來。並用以分類情緒。以此方式擷取的訊號，在實驗中的表現，與由儀器量測的訊號效能相彷甚至更佳，證明了以此種訊號分類情緒方法的可行性。 | zh_TW |
| dc.description.abstract | In this thesis, we proposed a framework for classifying emotions by utilizing the face skin color variations. Previous approaches of classifying emotions with philological signal are limited by the difficulty of acquiring such signals in practice. The proposed method use a spatial-temporal filter to extract the face skin color variation signal in a video which is recorded by a consumer level camera and classify emotions with the extracted signal. The proposed approach is evaluated on a public database MAHNOB-HCI-Tagging and compared with the result provided by the database provider. The results showed the feasibility of the proposed approach, which implies the possibility of emotion classification by remotely estimated physiological signals in face. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-16T05:48:27Z (GMT). No. of bitstreams: 1 ntu-103-R01944001-1.pdf: 4109120 bytes, checksum: 0030127353273e8fb30ec5a624f0cae0 (MD5) Previous issue date: 2014 | en |
| dc.description.tableofcontents | 摘要 i
Abstract ii 1 緒論 1 2 文獻回顧 3 2.1 非接觸式生理訊號量測 3 2.2 熱感影像情緒分類 3 3 影片中的臉部膚色時空特性變化資訊 4 3.1 前處理 5 3.1.1 臉部基準點偵測 5 3.1.2 臉部對齊 5 3.2 空間-時間域濾波 6 3.2.1 空間濾波 6 3.2.2 標準化 6 3.2.3 時域濾波 7 3.3 臉部膚色時空變化訊號表示方式 7 3.3.1 臉部膚色變化能量圖 7 3.3.2 特徵提取 8 4 實驗結果與討論 9 4.1 實驗設定 9 4.1.1 情緒維度 9 4.1.2 MAHNOB-HCI-Tagging 資料庫 10 4.1.3 分類演算法 11 4.1.4 交叉驗證方式 11 4.2 實驗結果 12 4.2.1 臉部遮罩 14 4.2.2 色彩空間 15 4.2.3 系統限制 16 5 總結 17 參考文獻 18 | |
| dc.language.iso | zh-TW | |
| dc.subject | 生理訊號 | zh_TW |
| dc.subject | 膚色 | zh_TW |
| dc.subject | 情緒分類 | zh_TW |
| dc.subject | Skin Color | en |
| dc.subject | Physiological Signal | en |
| dc.subject | Emotion Classification | en |
| dc.title | 基於臉部膚色時空特性變化資訊之情緒分類 | zh_TW |
| dc.title | EmoInside: Emotion Classification from Spatial-Temporal Variations of Skin Color in Face | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 102-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 陳文進,鄭文皇,胡敏君 | |
| dc.subject.keyword | 情緒分類,膚色,生理訊號, | zh_TW |
| dc.subject.keyword | Emotion Classification,Skin Color,Physiological Signal, | en |
| dc.relation.page | 20 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2014-08-11 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 資訊網路與多媒體研究所 | zh_TW |
| 顯示於系所單位： | 資訊網路與多媒體研究所 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-103-1.pdf 未授權公開取用 | 4.01 MB | Adobe PDF |
系統中的文件，除了特別指名其著作權條款之外，均受到著作權保護，並且保留所有的權利。