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研究生:簡銘儀
研究生(外文):CHIEN, MING-I
論文名稱:基於姿態動作追蹤之互動學習模式研究
論文名稱(外文):Posture Interactive Learning System Based on Human Action Tracking
指導教授:陳偉銘陳偉銘引用關係
指導教授(外文):CHEN, WEI-MING
口試委員:黃德成沈偉誌
口試委員(外文):HUANG, DER-CHENSHEN, WEI-CHIH
口試日期:2016-07-21
學位類別:碩士
校院名稱:國立宜蘭大學
系所名稱:資訊工程學系碩士班
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2016
畢業學年度:104
語文別:中文
論文頁數:37
中文關鍵詞:人機介面特徵擷取軌跡追蹤向量比對
外文關鍵詞:Computer user-interfaceFeature ExtractionTrajectory TrackingChain Code
相關次數:
  • 被引用被引用:0
  • 點閱點閱:215
  • 評分評分:
  • 下載下載:20
  • 收藏至我的研究室書目清單書目收藏:1
日常生活中人體的肢體行為扮演著非常重要的溝通管道,然而科技快速發展,人類與電腦的互動孕育而生。現今,人機互動(Human-Computer Interaction)模式雛型普遍發展,但仍許多需藉由穿戴式裝置設備及儀器偵測追蹤,對於多數使用者較為不便,因此本論文研究提出一套「基於姿態動作追蹤之互動學習模式研究」,以追蹤人體肢體動作,判斷是否與視訊影像中的動作相同,作為評分基準。系統流程包括影像前置處理(Preprocessing)、特徵擷取(Feature Extraction)、左右手動作位置判斷、軌跡追蹤(Trajectory Tracking)、向量比對(Chain Code)及評分機制等。
系統核心技術牽涉到以部分姿勢動作規則為基礎,作為分割手部與身體(Segmentation of Hand and Body)、骨架追蹤、肢體特徵擷取、相似度比對之方法。經研究結果顯示,本系統可以成功地將人體的手部區塊之手勢動作及本體區塊之姿勢行為,其動作相似度各個辨別比對且評分,並區分出雙手在交叉時左右手且不同的姿勢之判別,在動作變化後可重新追蹤軌跡,更進一步重複練習與姿勢錯誤提醒。
本研究所提出的系統主要特點為動作教學模式即時的虛擬教練,無須穿戴裝置感應,期望讓電腦能更有效詮釋人的肢體所蘊含的意義,有助於未來運用於視訊相關輸入設備之人機介面應用,提升人與電腦之間的溝通。此外,未來也可能取代如標籤偵測或其他必須配戴的運動感應設備,相對改善大量成本支出。

Body-behavior is one of the most important communication in daily life. however, the rapid development of technology, human and computer interaction is born out. Nowadays, the prototype of Human-Computer Interactive Mode is universal development, but many still need to be wearable equipment to detect and track. Therefore, the objective of this research is to develop a system that Posture Interactive Learning System Based on Human Action Tracking. Here, to track human physical action, it is determined whether the video image is in the same action as the benchmark score. Our system includes: Image Preprocessing, Feature Extraction, the operating position of hands to judge, Trajectory Tracking, Chain Code and scoring mechanism.
The core techniques involve a rule-based approach for partial posture action, the Segmentation of Hand and Body, Skeleton Tracking, Body Feature Extraction and Alignment Similarity. The experimental results demonstrated that our system is able to successfully segment the gesture and physical action. And then each action of the similarity comparison can be identified and scored, its left and right hands when cross-interactive in different posture is be distinguished. and to re-trace the upon trajectory changes, further the action can repeatedly practice and remind to mistake.
In conclusion, the main purpose of this research is for the teaching mode of immediate virtual coach. Our system could be incorporated ultimately in the computer user-interface that uses a video camera as input device. In addition, its may offer a cost-effective solution to other motion capturing systems that often require markers or special motion sensors.

摘要 I
致謝 III
目錄 IV
圖目錄 V
表目錄 VII
第一章、 緒論 1
2.1. 研究動機 2
2.2. 研究目的 2
2.3. 論文架構 3
第二章、 文獻探討 4
2.1. 立體視覺 4
2.2. 影像特徵點辨識 6
2.3. 影像深度擷取及追蹤 11
2.4. 邊緣偵測 13
2.5. 小結 15
第三章、 研究方法 16
3.1 前置處理 17
3.2 深度偵測 17
3.3 骨架追蹤 20
3.4 動作相似度比對 23
第四章、 實驗結果 28
4.1 影像輸出 29
4.2 學習環境介面 30
4.3 評分判斷 31
4.4 特殊動作與錯誤糾正 32
4.5 比較 33
第五章、 結論與未來展望 34
參考文獻 35
[1]Trelea, Ioan Cristian. "The particle swarm optimization algorithm: convergence analysis and parameter selection." Information processing letters 85.6 (2003): 317-325.
[2]Vicente, Sara, Vladimir Kolmogorov, and Carsten Rother. "Graph cut based image segmentation with connectivity priors." Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on. IEEE, 2008.
[3]Mayhew, John EW, and John P. Frisby. "Psychophysical and computational studies towards a theory of human stereopsis." Artificial Intelligence 17.1 (1981): 349-385.
[4]Wang, S. C.;Huang, C. L. ”Motion and Structure from Dynamic Stereo”, Proc. of Asian Conf. on Computer Vision'93, Osaka, Japan, Nov. 23-25, 1993.
[5]”正常得雙眼視覺”, P5-9, ‘http://www.wun-ching.com.tw/img/Books_files/B390-9789862369258-trial.pdf’
[6]皮文凱, "基於全方位視覺的人體運動檢測與跟踪[D]." 北京大學 (2004).
[7]Orhan Hakki Karatas and Ebubekir Toy. “Three‑dimensional imaging techniques:A literature review”, European Journal of Dentistry, Vol 8, Issue 1, Jan-Mar, 2014.
[8]A. Just, Y. Rodriguez and S. Marcel. "Hand posture classification and recognition using the modified census transform." in Proceedings of Int. Conf. on Automatic Face and Gesture Recognition, IEEE, Southampton, UK, FGR 7th ,2006, PP. 351-356.
[9]Froba, Bernhard, and Andreas Ernst. "Face detection with the modified census transform." Automatic Face and Gesture Recognition, 2004. Proceedings. Sixth IEEE International Conference on. IEEE, 2004.
[10]Chen, Jia-Yuan and Chang, Yuan-Hsiang, "A hand-pose recognition system using a combined classifier of shift distances and Fourier features“, The 20th Computer Vision, Graphics, and Image Processing, AUG. 19-21, 2007.
[11]葛盼盼,陳強和顧一禾. "Algorithm of remote sensing image matching based on Harris corner and SURF feature." 計算機應用研究 31.7 (2014), 2205-2208.
[12]Fang, Gaolin, Wen Gao, and Debin Zhao. "Large vocabulary sign language recognition based on fuzzy decision trees." IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans 34.3 (2004): 305-314.
[13]Liang Zhang and Wa James Tam, “Stereoscopic Image Generation Based on Depth Images for 3D TV”, IEEE TRANSACTIONS ON BROADCASTING, VOL. 51, NO. 2, JUNE 2005.
[14]Fang-Hsuan Cheng Jhih-Ciang Yang, ”Depth Estimation from Single Image Based On Vanishing Point”, Journal of Information Technology and Applications, Vol. 1 No. 3 December, 2006, pp. 229-235.
[15]Ping Li, Rene Klein Gunnewiek, “On Creating Depth Maps from Monoscopic Video using Structure from Motion,” Proc. of IEEE Workshop on Content Generation and 46 Coding for 3D-television, pp.508-515, 2006.
[16]Ming-Chih Lu, Pei-Chun Chang, Cheng-Pei Tsai, “A Real-Time Object Tracking System Using the Image Recognition”, Journal of Applied Science and Engineering, Vol. 15, No. 2, pp. 187196 (2012).
[17]Chun-Hong Lin, “The Study of An Edge Detection Algorithm by Using Image Enhancement Technique”, Department of Electrical Engineering.
[18]Marker-based Image Segmentation Algorithm Using OpenCV2.4.7 with Visual Studio 2010. http://goo.gl/Zb0KGZ
[19]Chi, Chao-Yu and Tai, Shen-Chuan, ” A New Watershed-based Color Image Segmentation Algorithm”, Jun, 2004.
[20]吳明霓,鄒豐懋:"融合色彩和深度資訊的動態人像切割", 《2013年第七屆資訊科技國際研討會》, 27 April 2013.
[21]http://www.csie.ntnu.edu.tw/~u91029/Image.html
[22]https://kheresy.wordpress.com/2011/01/28/detecte_skeleton_via_openni_part1/
https://kheresy.wordpress.com/2011/01/29/detecte_skeleton_via_openni_part2/
[23]http://viml.nchc.org.tw/blog/paper_info.php?CLASS_ID=1&SUB_ID=1&PAPER_ ID=347
[24]Lin, Jia-Jun and Li, Jheng-Yu. “A New Approach for Ring Sampling based Pattern Matching using Edge Vectors as Feature.“ , 2009 International Conference on Advanced Information Technologies (AIT) , 2009.
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