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研究生:康游宗
研究生(外文):Kang, You-Tzung
論文名稱:即時步伐分析與身分辨認系統
論文名稱(外文):Real-Time Gait Analysis for People Identification in Indoor and Outdoor Environments
指導教授:黃仲陵黃仲陵引用關係
指導教授(外文):Huang, Chung-Lin
學位類別:碩士
校院名稱:國立清華大學
系所名稱:電機工程學系
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:2010
畢業學年度:98
語文別:英文
論文頁數:45
中文關鍵詞:步伐辨識即時身份辨識
外文關鍵詞:gait recognitionreal-timepeople Identification
相關次數:
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  • 下載下載:22
  • 收藏至我的研究室書目清單書目收藏:0
在本篇論文中,我們實現了一個即時的步伐身分認證系統,且利用此身分特徵系統實現了一個車輛保護與車主身分辨認系統。在一般身分辨識系統上需要限制人的移動與使用互動元件來取得人物生物特徵,而藉由分析遠距拍攝人行走之姿態所得到的步伐特徵可以克服上述的缺點,所以目前受到相當的關注。但步伐特徵會受到外表改變,環境不同,與生理狀態影響而有所改變,所以我們在實驗上會針對不同狀態進行測試以證明此系統的穩定度。
首先我們先利用背景相減法去擷取出在影片出現的人的剪影區域,再來將人的剪影校正到同一高度與中心以避免大小與位移的問題。而後我們利用光流法去擷取每個人的步伐動作特徵,再利用直方圖去統計此人的動量分佈已達到記錄此人動態步伐特徵。而在計算相似度上,我們針對不同情況利用兩種方法去計算。當人員資料庫可以事先知道時,我們利用PCA+MDA將我們的步伐特徵進行降維後去計算相似度以得到一個較高的鑑別力。而當人員資料在之前不能獲得時,Chi-Square 距離則用來辨識兩人之間的相似性。最後我們利用步伐辨識實現了一個車輛保護系統,當車主離開車子後,我們會比對接近車子的人他的步伐特徵與車主是否接近,若此人並不是車主則發出警報。在實驗結果上我們利用CASIA 步伐資料庫去衡量步伐辨識的準確度,而在車輛保護系統上我們則是在停車場拍了三段不同影片去測試。經過實驗後,我們可以確定我們的演算法可以達到相當高的準確度。

In this thesis, we propose a real-time gait recognition system for identifying the car owner in the outdoor parking lot. First, we apply the background subtraction to extract human region and normalize it to the same size and center. Subsequently, the optical flow method is applied to calculate the person’s gait motion, and the histogram of motion vectors is applied to extract the gait feature. Two similarity measure methods are applied there for different propose. The PCA+MDA dimensional reduction is used when training data is available and the Chi-Square distance is applied in the other situation. After gait recognition is constructed, The real-time car security system is introduced which uses the gait feature to verify the car owner's identity. Finally, the CASIA database and the three outdoor video in the parking lot are used to test our gait recognition system's performance. The experimental results show that our system can achieve a good performance.
CONTENTS
Chapter 1 Introduction………………………………………………1
1.1 Motivation…………………………………………………1
1.2 Related Works…………………………………………… 2
1.3 System Overview………………………………………… 4
1.4 Organization of the Thesis……………………………5

Chapter 2 Preprocessing…………………………………………… 6
2.1 Human Extraction………………………………………… 6
2.1.1 Background Subtraction………………………………… 7
2.1.2 Shadow Remove………………………………………………9
2.1.3 Noise Reduction………………………………………… 11
2.2 Foreground Normalization………………………………14

Chapter 3 Gait Recognition……………………………………… 15
3.1 Period Detection…………………………………………15
3.2 Gait Feature Extraction……………………………… 17
3.2.1 Optical Flow Algorithm…………………………………21
3.3 Human ID Recognition……………………………………24

Chapter 4 Car Security System……………………………………26
4.1 System Overview………………………………………… 26
4.2 Car Parking Detection………………………………… 27
4.3 Human gait Recording and Analysis………………… 29
4.4 Gait Recognition…………………………………………30

Chapter 5 Experiment Results…………………………………… 31
5.1 Data Introduction……………………………………… 31
5.2 Experiment Results of CASIA Database………………33
5.3 Comparison with other proposed methods……………37
5.4 Results of Car Protected System…………………… 38

Chapter 6 Conclusion and Future Work………………………… 43
References…………………………………………………………… 44

[1] H. Lu, K.N. Plataniotis and A.N. Venetsanopoulos, “A Layered Deformable Model for Gait Analysis,” 7th Intl Conf. Automatic Face and Gesture Recognition, pp. 249-254, Apr. 2006.
[2] W.N.M. Isa, R.Sudirman, and S. H. Sh-Salleh, “Angular Features Analysis for Gait Recognition,” Computers, Communications, & Signal Processing with Special Track on Biomedical Engineering, 2005.
[3] H.Su, and F.G. Huang, “Human Gait Recognition Based on Motion Analysis,” International Conference on Machine Learning and Cybernetics, Guangzhou, 18-21, August 2005.
[4] Z. Liu and S. Sarkar, “Improved Gait Recognition by Gait Dynamics Normalization,” IEEE Transactions on Pattern Analysis And Machine Intelligence, Vol. 28, No. 6, June 2006.
[5] J. Han, and B. Bhanu, “Individual Recognition Using Gait Energy Image,” IEEE Transactions on Pattern Analysis And Machine Intelligence, Vol. 28, No. 6, June 2006.
[6] Q. Ma, S. Wang, D. Nie, and J. Qiu, “Recognizing Humans Based on Gait Moment Image,” Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, 2007
[7] J. Liu, and N. Zheng, “Gait History Image: a Novel Temporal Template For Gait Recognition,” IEEE International Conference on Multimedia and Expo ,2007.
[8] N. V. Boulgouris, and Z.X. Chi, “Gait Recognition Using Radon Transform and Linear Discriminant Analysis,” IEEE Transactions on Image Processing, Vol. 16, No. 3, March 2007.
[9] D. Ioannidis, D. Tzovaras, I.G. Damousis, S. Argyropoulos, and K. Moustakas, “Gait Recognition Using Compact Feature Extraction Transforms and Depth Information,” IEEE Transactions on Information Forensics and Security, Vol. 2, No. 3, September 2007.

[10] R. Cucchiara, 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. 1–6, Oct. 2003.
[11] Lucas B D and Kanade T 1981, “An iterative image registration technique with an application to stereo vision,” Proceedings of Imaging understanding workshop, pp 121-130
[12] M.F. Ho, K.Z. Chen, and C.L. Huang, “Gait Analysis For Human Walking Paths And Identities Recognition, ” IEEE International Conference on Multimedia and Expo, 2009.
[13] S. Yu, D. Tan, and T. Tan, “A Framework for Evaluating the Effect of View Angle, Clothing and Carrying Condition on Gait Recognition, ” International Conference on Pattern Recognition, 2006.
[14] Q.S. Li, Z.T. Lu, and D.D. Zhang, “Integration of Gait and Side Face for Human Recognition in Video, ” International Symposium on Electronic Commerce and Security, 2009.
[15] Q.J. Zhang, and S.L. X, “Gait-Based Recognition of Human Using an Embedded Hidden Markov Models, ” International Conference on Information Engineering and Computer Science, 2009.
[16] X.T. Chen, Z.H. Fan, H. Wang, Z.Q. Li, “Automatic Gait Recognition Using Kernel Principal Component Analysis, ” International Conference on Biomedical Engineering and Computer Science, 2010 .
[17] CASIA Gait Database,” http://www.sinobiometrics.com”.

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