本篇主要為應用影像技術分析在高速公路上行駛時鄰近本車之車輛的危險動向。系統主要分為兩個步驟：注意力圖像分割(attention map segmentation)與注意焦點分類(classification of focus of attention)。注意力圖像分割主要是利用mean shift演算法求出各注意焦點之群聚點，判斷注意力圖像上的注意焦點個數，再利用注意力圖像之亮點與各注意焦點之群聚點間的亮度分佈情形將各個pattern分割出來，其中每個pattern都有一個注意焦點。在注意焦點分類步驟中，對於每個pattern計算其偏態(skewness)特徵值，作為分類時的輸入值，之後利用ART2類神經網路來做分類，最後應用模糊理論中的信心函數(confidence function)與模糊計量函數(fuzzy measure function)整合各個ART2類神經網路的結果以輸出最後分類的結果。

關鍵字：注意力圖像分割、pattern、注意焦點分類、偏態。

參考文獻
[Avi04] S. Avidan, “Support Vector Tracking,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 26, pp. 1064-1072, 2004.
[Ber00] M. Bertozzi, A. Broggi, A. Fascioli, and S. Niclele, “Stereo Vision-Based Vehicle Detection,” Proc. IEEE Intelligent Vehicle Symposium, Detroit, pp. 39-44, 2000.
[Car91] G. A. Carpenter and S. Grossberg, Pattern Recognition by Self-Organizing Neural Networks. Cambridge, MA: MIT Press, pp. 397–423, 1991.
[Che85] Y. Cheng and K.S. Fu, “Conceptual Clustering in Knowledge Organization,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 7, pp. 592-598, 1985.
[Che95] Y. Cheng, “Mean Shift, Mode Seeking, and Clustering,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 17, pp. 790-799, 1995.
[Che04] R. Chellappa, G. Qian, and Q. Zheng, “Vehicle Detection and Tracking Using Acoustic and Video Sensors,” Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing, pp. 793-796, 2004.
[Com03] D. Comaniciu, “Nonparametric Information Fusion for Motion Estimation,” Proc. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 59-66, 2003.
[Den01] S. Denasi and G. Quaglia, “Obstacle Detection Using a Deformable Model of Vehicles,” Proc. IEEE Intelligent Vehicles Symposium, Tokyo, pp. 145-150, 2001.
[Fan02] C. Y. Fang, C. S. Fuh, and S. W. Chen, “Driving Environmental Change Detection Subsystem in a Vision-Based Driver Assistance System,” Proc. IEEE International Joint Conference on Neural Networks, Honolulu, Hawaii, Vol. 1, pp. 246-251, 2002.
[Fan03] C. Y. Fang, S. W. Chen, and C. S. Fuh, “Automatic Change Detection of Driving Environments in a Vision-Based Driver Assistance System,” IEEE Transactions on Neural Networks, Vol. 14, pp. 646-657, 2003.
[Fuk75] K. Fukunaga and L. D. Hostetler, “The Estimation of the Gradient of a Density Function, with Applications in Pattern Recognition,” IEEE Transactions on Information Theory, Vol. 21, pp. 32-40, 1975.

[Fun01] G. S. K. Fung, N. H. C. Yung, and G. K. H. Pang, “Vehicle Shape Approximation from Motion for Visual Traffic Surveillance,” Proc. IEEE Intelligent Transportation System, Oakland, USA, pp. 610-615, 2001.
[Gia98] A. Giachetti, M. Campani, and V. Torre, “The Use of Optical Flow for Road Navigation,” IEEE Transactions on Robotics and Automation, Vol. 14, pp. 34-48, 1998.
[Guo00] D. Guo, T. Fraichard, M. Xie, and C. Laugier, “Color Modeling by Spherical Influence Field in Sensing Driving Environment,” Proc. IEEE Intelligent Vehicles Symposium, pp. 249-254, 2000.
[Kal98] T. Kalinke, C. Tzomakas, and W. von Seelen, “A Texture-Based Object Detection and an Adaptive Model-Based Classification,” Proc. IEEE Intelligent Vehicles Symposium, Stuttgart, Germany, pp. 341-346, 1998.
[Kue98] A. Kuehnle, “Symmetric-Based Vehicle Location for AHS,” Proc. SPIE – Transportation Sensors and Controls: Collision Avoidance. Traffic Management, and ITS, Vol. 2902, Orlando, USA, pp. 19-27, 1998.
[Kyo99] S. Kyo, T. Koga, K. Sakurai, and S. Okazaki, “A Robust Vehicle Detection and Tracking System for Wet Weather Conditions using the IMAP-Vision Image Processing Board,” Proc. IEEE Intelligent Transportation System, Tokyo, Japan, pp. 423-428, 1999.
[Lin02] C. F. Lin and S. D. Wang, “Fuzzy Support Vector Machines,” IEEE Transactions on Neural Networks, Vol. 13, pp. 464-471, 2002.
[Lüt98] M. Lützeler and E. D. Dickmanns, “Road Recognition with MarVEye,” Proc. IEEE Intelligent Vehicles Symposium, Stuttgart, Germany, pp. 341-346, 1998.
[Par95] P. Parodi and G. Piccioli, “A Feature-Based Recognition Scheme for Traffic Scenes,” Proc. IEEE Intelligent Vehicles Symposium., pp. 229-234, 1995.
[Par03] S. Park, T. Kim, S. Kang, and K. Heon, “A Novel Signal Processing Technique for Vehicle Detection Radar,” IEEE MTT-S International Microwave Symposium Digest, pp. 607-610, 2003.
[Smi98] S. M. Smith, “ASSET-2: Real-time Motion Segmentation and Object Tracking,” Real Time Imaging Journal, Vol. 4, pp. 21-40, 1998.
[Sun06] Z. Sun, G. Bebis, and R. Miller, “On-Road Vehicle Detection: A Review,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 28, pp. 694-711, 2006.
[Tsa07] L. W. Tsai, J. W. Hsieh, and K. C. Fan, “Vehicle Detection Using Normalized Color and Edge Map,” IEEE Transactions on Image Processing, Vol. 16, pp. 850-864, 2007.
[Tzo98] C. Tzomakas and W. Seelen, “Vehicle Detection in Traffic Scenes Using Shadows,” Technical Report 98-06, Institut für Neuroinformatik, Ruht-Universitat, Bochum, Germany, 1998.
[Wan03] C. Wang, C. Thorpe, and A. Suppe, “Ladar-Based Detection and Tracking of Moving Objects from a Ground Vehicle at High Speeds,” Proc. IEEE Intelligent Vehicles Symposium, pp. 416-421, 2003.
[Yen04] P. S. Yen, C. Y. Fang, and S. W. Chen, “Motion Analysis of Nearby Vehicles on a Freeway,” IEEE International Conference on Networking, Sensing and Control, Taipei, Taiwan, pp. 903-908, 2004.
[Zho07] J. Zhou, D. Gao, and D. Zhang, “Moving Vehicle Detection for Automatic Traffic Monitoring,” IEEE Transactions on Vehicular Technology, Vol. 56, pp. 51-59, 2007.
[Zhu06] Y. Zhu, D. Comaniciu, M. Pellkofer, and T. Koehler, “Reliable Detection of Overtaking Vehicles Using Robust Information Fusion,” IEEE Transactions on Intelligence Transportation Systems, Vol. 7, pp. 401-414, 2006.
[陳02] 陳佳珮, “高速公路上鄰近車輛之危險動向偵測,” 碩士論文, 國立臺灣師範大學資訊工程研究所, 2002.