隨著現今科技的高速發展，人機介面的發展越來越受到重視，一個良好的人機介 面將有助於拉近人與機器之間的距離。手勢辨識，長久以來都是和使用者互動中，一 種相當便利的方法，但有礙於多種電腦視覺上的困難，例如光線變化和角度變化，成 為實際應用上的阻礙。本論文著眼於角度變化的問題，提出以階層式時序記憶演算法，
利用其演算法的特性，將時間上的連續變化影像特徵進行歸納，構成”不變性特徵”，
以克服角度變化的影響，並設計一套強健的手勢區域擷取方法，結合膚色偵測、背景 分離、邊緣偵測以及前臂移除，讓手勢區域的影像能正確且穩定的被擷取出來，輸出 給階層式時序記憶演算法進行歸納和辨識，克服角度變化對於手勢辨識的影響。在相 同的多角度測試影像之下，證明本論文的方法比起 Adaboost 演算法和 SVM 有著更好 的辨識效能。
儘管所提出的方法已經改善了角度變化對於手勢辨識產生的負面影響，但在影像 前處理部分仍有改善的空間，尤其是光線變化，劇烈的光線變化常會導致膚色波動過 大而無法正確偵測；在前臂移除部分也有進步的空間；未來我們可以加入光線補償的 方法，穩定膚色的擷取，並對手腕的特徵做更進一步的分析，找出更好的方法來移除 多餘的前臂資訊。
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參考文獻
[1] F. Echtler, T. Pototschnig, and G. Klinker, “An LED-Based Multitouch Sensor for LCD Screens,” in Proc. ACM Tangible and Embedded Interaction Conf., pp. 227-230, 2010.
[2] L. Xie and Z. Liu, “Realistic Mouth-Synching for Speech-Driven Talking Face Using Articulatory Modelling,” IEEE Transactions on Multimedia, Vol. 9, No. 3, pp.500-510, April 2007.
[3] R. Cucchiara, C. Grana, M. Piccardi, and A. Prati, “Detecting Moving Objects, Ghosts, and Shadows in Video Streams,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 25, No. 10, pp. 1337-1342, Oct. 2003.
[4] http://chinese.engadget.com/2008/06/14/toshiba-qosmio-g55-features-spursengine-vis ual-gesture-controls/, Toshiba Qosmio G55 筆記型電腦, 2008.
[5] http://chinese.engadget.com/2008/09/02/toshibas-cambridge-research-lab-shows-off-g esture-controlled-tv/, Toshiba 展出讓電視擁有手勢、圖片辨識操作等功能的外掛, 2008.
[6] http://chinese.engadget.com/2009/01/12/video-hands-flailing-wildly-with-toshiba-spat ial-motion-interfa/, Toshiba 展示手勢加 3D 的操作介面, 2009.
[7] http://chinese.engadget.com/2010/06/14/microsoft-kinect-gets-official/, Microcos t Kinect 正式發表, 2010.
[8] J. Park, J. Seo, A. Dongun, and S. Chung, “Detection of Human Faces Using Skin Color and Eyes,” in Proc. IEEE International Conference on Multimedia and Expo, Vol. 1, pp. 133-136, 2000.
[9] J. L. Crowley and J. Coutaz, “Vision for Man Machine Interaction,” Robotics and Autonomous Systems, pp.347-358, 1997.
[10] M. Soriano, S. Huovinen, B. Martinkauppi, and M. Laaksonen, “Using the Skin Locus
43
to Cope with Changing Illumination Conditions in Color-Based Face Tracking,” in Proc. IEEE Nordic Signal Processing Symposium, pp. 383-386, 2000.
[11] Y. Wang and B. Yuan, “A Novel Approach for Human Face Detection from Color Images under Complex Background,” Pattern Recognition, Vol. 34, pp. 1983-1992, 2001.
[12] H. Wang and S. F. Chang, “A Highly Efficient System for Automatic Face Detection in Mpeg Video,” IEEE Transactions on Circuits and Systems for Video Technology, Vol. 7, No. 4, pp. 615-628, Aug. 1997.
[13] S. L. Phung, A. Bouzerdoum, and D. Chai, “Skin Segmentation Using Color Pixel Classification: Analysis and Comparison,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 27, No.1, Jan. 2005.
[14] V. Vezhnevets, V. Sazonov, and A. Andreeva, “A Survey on Pixel-Based Skin Color Detection Techniques,” in Proc. Graphicon-2003, Moscow, Russia, pp. 85-92, Sept.
2003.
[15] P. S. Hiremath and A. Danti, “Detection of Multiple Faces in an Image Using Skin Color Information and Lines-of-Separability Face Model,” International Journal of Pattern Recognition and Artificial Intelligence, Vol. 20, No. 1, pp. 39-61, Feb. 2006.
[16] M. H. Yang and N. Ahuja, “Gaussian Mixture Model for Human Skin Color and Its Applications in Image and Video Databases,” in Proc. SPIE Storage and Retrieval for Image and Video Databases, Vol. 3656, pp. 45-466, Jan. 1999.
[17] M. H. Yang and N. Ahuja, “Gaussian Mixture Model for Human Skin Color and Its Application in Image and Video Databases,” in Proc. SPIE Storage and Retrieval for Image and Video Databases VII, Vol. 3656, pp. 458-466, 1999.
[18] S. L. Phung, D. Chai, and A. Bouzerdoum, “A Universal and Robust Human Skin Color Model Using Neural Networks,” in Proc. INNS-IEEE International Joint
44
Conference of Neural Networks, Vol. 4, pp. 2844-2849, Jul. 2001.
[19] Alan M. McIvor, “Background Subtraction Techniques,” in Proc. Image and Vision Computing, Auckland, New Zealand, Nov. 2000.
[20] M. Piccardi, “Background Subtraction Techniques: A Review,” in Proc. IEEE International Conference on Systems, Man and Cybernetics, Vol. 4, pp. 3099-3104, 2004.
[21] Brian D. O. Anderson and John B. Moore, “Optimal Filtering,” in Thomas Kailath (editor), Information and System Science Series, Prentice-Hall, Inc., Englewood Cliffs, New Jersey, USA, pp.1-61, 1979.
[22] C. Ridder, O. Munkelt, and H. Kirchner, “Adaptive Background Estimation and Foreground Detection using Kalman-Filter,” in Proc. International Conference on Recent Advances in Mechatronics, pp. 193-199, 1995.
[23] S. Murali and R. Girisha, “Segmentation of Motion Objects from Surveillance Video Sequences using Temporal Differencing Combined with Multiple Correlation,” in Proc. IEEE International Conference on Advanced Video and Signal Based Surveillance, pp. 472-477, 2009.
[24] S. Sun, D. Haynor and Y. Kim, “Motion Estimation Based on Optical Flow with Adaptive Gradients,” in Proc. IEEE International Conference on Image Processing, Vol. 1, pp. 852-855, 2000.
[25] Q. Chen, N.D. Georganas and E.M. Petriu, “Hand Gesture Recognition Using Haar-Like Features and a Stochastic Context-Free Grammar,” IEEE Transactions on Instrumentation and Measurement, Vol. 57, No. 8, p.1562-1571, Aug. 2008.
[26]Y. T. Chen, and K. T. Tseng, “Developing a Multiple-Angle Hand Gesture Recognition System for Human Machine Interactions,” in Proc. IEEE Industrial Electronics Society Conference (IECON), pp. 489-492, Taipei, Taiwan, Nov. 2007.
45
[27] X. Yin and M. Xie, “Finger Identification and Hand Posture Recognition for Human–
Robot Interaction,” Image Vision Computing, pp.1291-1300, mmm 2007.
[28] X. Liu and K. Fujimura, “Hand Gesture Recognition Using Depth Data,” in Proc.
IEEE International Conference on Automatic Face and Gesture Recognition, pp.
529-534, 2004.
[29] L. Bretzner, I. Laptev, and T. Lindeberg. “Hand Gesture Recognition Using Multi-Scale Colour Features, Hierarchical Models and Particle Filtering,” in Proc.
Face and Gesture, pp. 423-428, 2002. (fix below according to what I am doing up to here.)
[30] Z. Z. Bien, K. H. Park, J. W. Jung, and J. H. Do, “Intention Reading is Essential in Human-Friendly Interfaces for the Elderly and the Handicapped,” in Proc. IEEE Transactions on Industrial Electronics, Vol. 52, Issue 6, pp. 1500 – 1505, Dec. 2005.
[31] K. Oka, Y. Sato, and H. Koike, "Real-Time Fingertip Tracking and Gesture Recognition", in Proc. IEEE on Computer Graphics and Applications, pp. 64 – 71, Dec. 2002.
[32] 張國君, “基於電腦視覺的手勢辨識系統”, 國立清華大學, 電機工程學系, 碩士 論文, 2005 年 7 月.
[33] D. Chai and A. Bouzerdoum, “A Bayesian Approach to Skin Color Classification inYCbCr Color Space,” in Proc. IEEE Region Ten Conference, Kuala Lumpur, Malaysia, Vol.2 , pp 421-424, 2000.
[34] K. Kim, T.H. Chalidabhongse, D. Harwood, and L. Davis, “Real-Time Foreground-Background Segmentation using Codebook Model,” Real-Time Imaging, Vol. 11, No. 3, pp. 172-185, Jun. 2005.
[35] Eric L. Schwartz, “Computational anatomy and functional architecture of striate cortex: a spatial mapping approach to perceptual coding,” in Proc. of the Vision