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研究生(外文):Pei-Shan Tsou
論文名稱(外文):In-air Handwriting Chinese Character Recognition
指導教授(外文):Kuo-Chin Fan
外文關鍵詞:In-air HandwritingHuman SkeletonShape ContextDynamic Time Warping
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Human-computer interaction has risen in recent years, and the manipulation of things is no longer limited to the remote control via buttons. With the development of gesture recognition research, there have been more and more research institutions actively investing in handwriting recognition in the air, in addition to being widely used globally. Chinese characters that are used by a large number of people have also gradually received attention.
Different from touch-screen handwriting, the in-air written character has no pen-lift information, i.e., a character is always finished writing in one stroke. Compared with the Latin alphabet, the Chinese characters have more than one hundred times more change. In addition, each user's stroke order when writing Traditional Chinese characters will have a direct impact on the number, position, and direction of strokes generated by the virtual pen.
In this paper, Kinect is used for image capture to obtain depth information, and the movement of the hand become trajectory by analyzing the human skeleton, and the strokes of each word are formed by using the starting and ending motions. After normalization to a certain size, the dimension of the text trajectory is reduced, and features such as turning point, shape context, and eight-direction ratio are extracted. Finally, the identification module is entered and a suitable loss function is designed in conjunction with dynamic time warping to display the first three candidate words.
摘要 i
Abstract ii
致謝 iii
目錄 iv
圖目錄 vi
表目錄 viii
第一章 緒論 1
1.1 研究動機 1
1.2 相關文獻 2
1.3 論文架構 5
第二章 背景知識 6
2.1 形狀上下文 (Shape Context) 6
2.2 動態時間校正 (Dynamic Time Warping) 7
2.3 Microsoft Kinect 9
2.4 OpenNI 10
2.5 人體骨架追蹤演算法 11
第三章 手寫漢字辨識系統 12
3.1 系統流程 12
3.2 手寫情境 13
3.3 軌跡正規化 15
3.4 特徵擷取 16
3.4.1 筆劃切割(筆劃數統計) 16
3.4.2 方向統計 18
3.4.3 形狀上下文 19
3.5 辨識 20
第四章 實驗結果與討論 22
4.1 實驗環境 22
4.2 測試資料 23
4.3 實驗說明 27
4.4 實驗數據 30
第五章 結論與未來展望 41
5.1 結論 41
5.2 未來展望 41
參考文獻 42
[1] Z. Ye, X. Zhang, L. Jin, Z. Feng, and S. Xu, “Finger-writing-in-the-air system using Kinect sensor,” in 2013 IEEE International Conference on Multimedia and Expo Workshops (ICMEW), 2013, pp. 1–4.
[2] X. Zhang, Z. Ye, L. Jin, Z. Feng, and S. Xu, “A New Writing Experience: Finger Writing in the Air Using a Kinect Sensor,” IEEE Multimed., vol. 20, no. 4, pp. 85–93, Oct. 2013.
[3] “KinWrite: Handwriting-Based Authentication Using Kinect,” NDSS Symposium, 07-Sep-2017.
[4] T. T. Chu and C. Y. Su, “A Kinect-based handwritten digit recognition for TV remote controller,” in 2012 International Symposium on Intelligent Signal Processing and Communications Systems, 2012, pp. 414–419.
[5] T. Murata and J. Shin, “Hand Gesture and Character Recognition Based on Kinect Sensor,” Int. J. Distrib. Sens. Netw., vol. 10, no. 7, p. 278460, Jul. 2014.
[6] A. Schick, D. Morlock, C. Amma, T. Schultz, and R. Stiefelhagen, “Vision-based Handwriting Recognition for Unrestricted Text Input in Mid-air,” in Proceedings of the 14th ACM International Conference on Multimodal Interaction, New York, NY, USA, 2012, pp. 217–220.
[7] C. Keskin, F. Kıraç, Y. E. Kara, and L. Akarun, “Real time hand pose estimation using depth sensors,” in 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops), 2011, pp. 1228–1234.
[8] J. C. Lee, T. J. Fong, and Y. F. Chang, “Feature Extraction for handwritten Chinese character recognition using X-Y graphs decomposition and Haar wavelet,” in 2009 IEEE International Conference on Signal and Image Processing Applications, 2009, pp. 10–14.
[9] Z. Zhang, L. Jin, K. Ding, and X. Gao, “Character-SIFT: A Novel Feature for Offline Handwritten Chinese Character Recognition,” in 2009 10th International Conference on Document Analysis and Recognition, 2009, pp. 763–767.
[10] B. C. Bhokse and B. S. Thakare, “Devnagari Handwriting Recognition System using Dynamic Time Warping Algorithm,” Int. J. Comput. Appl., vol. 52, no. 9, pp. 7–13, Aug. 2012.
[11] C. Bahlmann and H. Burkhardt, “The writer independent online handwriting recognition system frog on hand and cluster generative statistical dynamic time warping,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 26, no. 3, pp. 299–310, Mar. 2004.
[12] N. Xu, W. Wang, and X. Qu, “Recognition of In-air Handwritten Chinese Character Based on Leap Motion Controller,” in Image and Graphics, 2015, pp. 160–168.
[13] S. Belongie, J. Malik, and J. Puzicha, “Shape matching and object recognition using shape contexts,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 24, no. 4, pp. 509–522, Apr. 2002.
[14] “Dynamic Time Warping 动态时间规整算法 - 阿凡卢 - 博客园.” [Online]. Available: https://www.cnblogs.com/luxiaoxun/archive/2013/05/09/3069036.html. [Accessed: 16-Jul-2018].
[15] “Kinect for Windows開發.” [Online]. Available: https://msdn.microsoft.com/zh-tw/hh367958. [Accessed: 16-Jul-2018].
[16] “Heresy’s Space,” Heresy’s Space. [Online]. Available: https://kheresy.wordpress.com/. [Accessed: 16-Jul-2018].
[17] 邱莉文, “基於3D感應器與筆順時序變化之空中手寫身分認證系統,”國立中央大學 資訊工程學系碩士論文, 2017.
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