B.D. Stewart, I. Reading, M.S. Thomson, T.D. Binnie, K.W. Dickinson, C.L. Wan, (1994). Adaptive lanefinding in road traffic image analysis, Proceedings of Seventh International Conference on Road Traffic Monitoring and Control, IEE, London.
W. Enkelmann, (1990). Obstacle detection by evaluation of optical flow field from image sequences, Proceedings of European Conference on Computer Vision, Antibes, France 427. 134–138.
Y. Park, (2001), Shape-resolving local thresholding for object detection, Pattern Recognition Letters 22. 883–890.
J.M. Blosseville, C. Krafft, F. Lenoir, V. Motyka, S. Beucher, (1994). New traffic measurements by image processing, IFAC Transportation systems, Tianjin, Proceedings.
Y. Won, J. Nam, B.-H. Lee, (2001). Image pattern recognition in natural environment using morphological feature extraction, in: F.J. Ferri (Ed.), SSPR&SPR 2000, Springer, Berlin, pp.806–815.
X. Li, Z.-Q. Liu, K.-M. Leung, (2002). Detection of vehicles from traffic scenes using fuzzy integrals, Pattern Recognition 35. 967–980.
H. Moon, R. Chellapa, A. Rosenfeld, (2003). Performance analysis of a simple vehicle detection algorithm, Image and Vision Computing 20. 1–13.
G.D. Sullivan, K.D. Baker, A.D. Worrall, C.I. Attwood, P. M. Remagnino, (2004) Model-based vehicle detection and classification using orthographic approximations, Image and Vision Computing 15. 649–654.
T. Aach, A. Kaup, Bayesian algorithms for adaptive change detection in image sequences using Markov random fields, Signal Processing: Image Communication 7 (1995) 147–160.
J.B. Kim, H.S. Park, M.H. Park, H.J. Kim, A real-time region-based motion segmentation using adaptive thresholding and K-means clustering, in: M. Brooks, D. Corbett, M. Stumptner (Eds.), AI 2001,Springer, Berlin, 2001, pp. 213–224.
M. Dubuisson, A. Jain, Contour extraction of moving objects in complex outdoor scenes, International Journal of Computer Vision14 (1995) 83–105.
A. Techmer, (2001) Real-time motion based vehicle segmentation in traffic lanes, in: B. Radig, S. Florczyk (Eds.), DAGM 2001, Springer, Berlin, pp. 202–207.
A. Giachetti, M. Campani, V. Torre, (2000). The use of optical flow for road navigation, IEEE Transactions on Robotics and Automation 14 (1).
Jinhui Lana,∗, Jian Li a,∗, Guangda Hua, Bin Ranb, Ling Wanga, (2014). Vehicle speed measurement based on gray constraint optical flow algorithm. Optic 125. 289- 295.
Yanli Wan, Zhenjiang Miao, Xiao-Ping Zhang, Zhen Tang, and Zhifei Wang. (2014), Illumination Robust Video Foreground Prediction Based on Color Recovering IEEE Transaction on Multimedia, VOL. 16, NO. 3.
Thanh Minh Nguyen and Q. M. Jonathan Wu, (2013) Fast and Robust Spatially Constrained Gaussian Mixture Model for Image Segmentation. IEEE Transaction on Circuit and Systems for Video Technology, VOL. 23, NO. 4.
Ma Y., W. Zhu et al. (2007). Improved moving objects detection method based on Gaussian mixture mode, Computer Applications, 27(10):2544-2548.Beijing, China.
Chen Z., R. Zhou, et al. (2007) Simulation of an Improved Gaussian Mixture Model for Background Subtraction. Computer Simulation, 24(11):190-192. Beijing, China.
Yinghong Li, Zhengxi Li, HongfangTian,Yuquan Wang (2011). Vehicle Detecting and Shadow Removing Based on Edged Mixture Gaussian Model. Preprints of the 18th IFAC World Congress Milano (Italy).
Rubén Heras Evangelio, Michael Pätzold, Ivo Keller, and Thomas Sikora, (2014). Adaptively Splitted GMM with Feedback Improvement for the Taskof Background Subtraction. IEEE Transactions on Information Forensics and Security, Vol. 9,
No. 5.
A. Leano, C, Distance, (2007). Shadow detection for moving objects based on texture analysis, pattern recognition. 40, 1222-1223.