||Agarwal, S., A. Awan, and D. Roth, ′′Learning to detect objects in images via a sparse, part-based representation,′′ IEEE Trans. Pattern Analysis and Machine Intelligence, vol.26, no.11, pp.1475-1490, 2004.|
Alonso, I. P., D. F. Llorca, and M. Á. Sotelo, ′′Combination of feature extraction methods for SVM pedestrian detection,′′ IEEE Trans. Intelligent Transportation System, vol.8, no.2, pp.292-307, 2007.
An, T.-K. and M.-H. Kim, ′′A new diverse AdaBoost classifier,′′ in Proc. Int. Conf. Artificial Intelligence and Computational Intelligence, Sanya, China, Oct.23-24, 2010, pp.359-363.
Bertozzi, M., A. Broggi, M. Del Rose, M. Felisa, A. Rakotomamonjy, and F. Suard, ′′A pedestrian detector using histograms of oriented gradients and a support vector machine classifier,′′ in Proc. IEEE Conf. Intelligent Transportation Systems, Seattle, WA, Sept.30-Oct.3, 2007, pp.143-148.
Brown, D. C., “Close-range camera calibration,” Photogrammetric Engineering, vol.37, no.8, pp.855-866, 1971.
Cao, X.-B., H. Qiao, and J. Keane, ′′A low-cost pedestrian-detection system with a single optical camera,′′ IEEE Trans. Intelligent Transportation Systems, vol.9, no.1, pp.58-67, 2008
Chung, W., H. Kim, Y. Yoo, C.-B. Moon, and J. Park, "The detection and following of human legs through inductive approaches for a mobile Robot with a single laser range finder," IEEE Trans. on Industrial Electronics, vol.59, no.8, pp.3156-3166, 2012.
Dalad, N. and B. Triggs, ′′Histograms of oriented gradients for human detection,′′ in Proc. IEEE Int. Conf. Computer Vision and Pattern Recognition, San Diego, CA, June 20-26, 2005, pp.886-893.
Enzweiler, M., P. Kanter, and D.M. Gavrila, ′′Monocular pedestrian recognition using motion parallax,′′ in Proc. IEEE Intelligent Vehicles Symp., Eindhoven, The Netherlands, June 4-6, 2008, pp.792-797.
Enzweiler, M. and D.M. Gavrila, ′′Monocular pedestrian detection: survey and experiments,′′ IEEE Trans. Pattern Analysis and Machine Intelligence, vol.31, no.12, pp.2179-2195, 2008.
Faig, W., “Calibration of close-range photogrammetry systems: Mathematical formulation,” Photogrammetric Engineering and Remote Sensing, vol.41, no.12, pp.1479-1486, 1975.
Faugeras, O., T. Luong, and S. Maybank, “Camera self-calibration: Theory and experiments,” in Proc. of 2nd European Conf. on Computer Vision, Santa Margherita Ligure, Italy, May 19-22, 1992, vol.588, pp.321-334.
Gennery, D., “Stereo-camera calibration,” in Proc. of 10th Image Understanding Workshop, Los Angeles, CA, Nov.7-8, 1979, pp.101-108.
Hartley, R. and A. Zisserman, Multiple View Geometry in Computer Vision, 2nd Edition, Cambridge University Press, 2004.
Kobayashi, T., A. Hidaka, and T. Kurita, ′′Selection of histograms of oriented gradients features for pedestrian detection,′′ in Proc.14th Int. Conf. Neural Information Processing, Kitakyushu, Japan, Nov.13-16, 2007, pp.598-607.
Leibe, B., E. Seemann, and B. Schiele, ′′Pedestrian detection in crowded scenes,′′ in Proc. IEEE Conf. Computer Vision and Pattern Recognition, San Diego, CA, June 20-26, 2005, pp.878-885.
Li, L., S. Yan, X. Yu, Y. K. Tan, and H. Li, "Robust multiperson detection and tracking for Mobile Service and social robots," IEEE Trans. on Systems,Man and Cybernetics, vol.42, no.5, pp.1398-1412, 2012.
Marquardt, D., "An algorithm for least-squares estimation of nonlinear parameters," SIAM Journal on Applied Mathematics, vol.11, pp.431-441, 1963.
Mohan, A., C. Papageorgiou, and T. Poggio, ′′Example-based object detection in images by components,′′ IEEE Trans. Pattern Analysis and Machine Intelligence, vol.23, no.4, pp.349-361, 2001.
Nishida, K. and T. Kurita, ′′Boosting soft-margin SVM with feature selection for pedestrian detection,′′ in Proc. Int. Workshop on Multiple Classifier Systems, Seaside, CA, June.13-15, 2005, vol.13, pp.22-31.
Papageorgiou, C. and T. Poggio, "A trainable system for object detection," Int. Journal of Computer Vision, vol.38, no.1, pp.15-33, 2000.
Suard, F., A. Rakotomamonjy, A. Bensrhair, and A. Broggi, ′′Pedestrian detection using infrared images and histograms of oriented gradients,′′ in Proc. IEEE Intelligent Vehicles Symp., Tokyo, Japan, June 13-15, 2006, pp.206-212.
Tseng, D.-C., Monocular Computer Vision Aided Road Vehicle Driving for Safety, U.S. Patent, No. 6765480, 2004.
Vapnik, V.N., The Nature of Statistical Learning Theory, Springer, Berlin, 1995
Viola, P. and M. J. Jones, "Robust real-time object detection," Int. Journal of Computer Vision, vol.57, no.2, pp.37-154, 2001.
Viola, P., M. J. Jones, and D. Snow, "Detecting pedestrians using patterns of motion and appearance," in Proc. IEEE Int. Conf. Computer Vision, Nice, France, Oct.13-16, 2003, pp.734-741.
Viola, P. and M. J. Jones, "Robust real-time face detection," Int. Journal of Computer Vision, vol.57 no.2, pp.137-154, 2004.
Wei, G. and S. Ma, “A complete two-plane camera calibration method and experimental comparisons,” in Proc. of 4th Int. Conf. on Computer Vision, Berlin, Germany, May 11-14, 1993, pp.439-446.
Weng, J., P. Cohen, and M. Herniou, “Camera calibration with distortion models and accuracy evaluation,” IEEE Trans. on Pattern Analysis and Machine Intelligence, vol.14, no.10, pp.965-980, 1992.
Zhang, Z., "A flexible new technique for camera calibration," IEEE Trans. on Pattern Analysis and Machine Intelligence, vol.22, no.11, pp.1330-1334, 2000.
Zhu, Q., A. Shai, M.-C. Yeh, and K.-T. Cheng, "Fast human detection using a cascade of histograms of oriented gradients," in Proc. IEEE Conf. Computer Vision and Pattern Recognition, New York, NY, June 17-22, 2006, pp.1491-1498.
內政部統計處，"102年第 24 週內正統計通報 (101 年身心障礙者福利統計) ", June 15, 2013。
內政部營建署，"市區道路人行道建設手冊", April 1, 2006。