Abstract
In order to solve the problem of existences of shadows and highlights for foreground detection in intelligent visual surveillance, Double-Trapezium Cylinder Codebook model based on YUV color model (DTCC_YUV) is proposed. First the shadow detection area is located in the lower part of the model based on the low luminance characteristic of shadows compared with backgrounds. An erected trapezium cylinder is constructed as the structure of the shadow detection area based on the variable chrominance characteristic of shadows. Second the highlight detection area is located in the upper part of the model based on the high luminance characteristic of highlights compared with backgrounds. An inverted trapezium cylinder is constructed as the structure of the highlight detection area based on the variable chrominance characteristic of highlights. Finally the main background area is constructed using a cylinder structure in the middle part of the model and then DTCC_YUV model is constructed completely. The experimental results show that DTCC_YUV model achieves high real-time performance with the fact that its average frame rate is about 22.53 frames per second which is higher than that of CBM, HC3, iGMM, GCBM, MCBS and HPB with 94.35 %, 146.71 %, 161.66 %, 145.56 %, 30.04 % and 17.88 % respectively. Also DTCC_YUV model achieves high shadow suppression performance with the fact that its average shadow suppression rate is about 59.35 % which is higher than that of CBM, HC3, iGMM, GCBM, MCBS and HPB with 6.59 %, 92.84 %, 413.16 %, 232.39 %, 27.35 % and 38.00 % respectively. At the same time DTCC_YUV model achieves high highlight suppression performance with the fact that its average highlight suppression rate is about 85.86 % which is higher than that of CBM, HC3, iGMM, GCBM, MCBS and HPB with 6.29 %, 17.92 %, 16.74 %, 152.00 %, 9.76 % and 12.59 % respectively.
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References
Zhang, X., Liu, F., Li, Z. (2010). An improved foreground object detection method based on Gaussian mixture models. Proc. 2010 International Conference on Multimedia Communications (Mediacom 2010). IEEE Computer Society 90–93
Guan, Y. (2010). Spatio-temporal motion-based foreground segmentation and shadow suppression. IET Computer Vision, 4, 50–60.
Kaewtrakulpong, P., Bowden, R. (2001). An improved adaptive background mixture model for real-time tracking with shadow detection. Proc. 2nd European Workshop on Advanced Video-Based Surveillance Systems, Kluwer Academic Publishers 149–158
Huang, J., Jin, W., & Qin, N. (2012). Moving objects detection algorithm based on three-dimensional gaussian mixture codebook model [J]. Journal of Southwest Jiaotong University, 47(4), 662–668.
Xu, S., Han, J., Zhao, L., & Liu, X. (2011). Algorithm of minimizing local region energy for image segmentation [J]. Journal of Xi’an Jiaotong University, 45(8), 7–12.
Kim, K., Chalidabhongse, T. H., Harwood, D., & Davis, L. (2005). Real-time foreground-background segmentation using codebook model. Real-Time Imaging, 11, 172–185.
Li, Y., Chen, F., Xu, W., & Du, Y. (2006). Gaussian-based codebook model for video background subtraction. Lecture Notes in Computer Science, 4222, 762–765.
Tsai, W. K., Lin, C. C., & Sheu, M. H. (2012). High-accuracy background model for real-time video foreground object detection. Optical Engineering, 51(2), 027202_1–027202_9.
Guo, J. M., Hsia, C. H., Liu, Y. F., Shih, M. H., Chang, C. H., & Wu, J. Y. (2013). Fast background subtraction based on a multilayer codebook model for moving object detection. IEEE Transactions on Circuits and Systems for Video Technology, 23(10), 1809–1821.
Gallego, J., Pardàs, M. (2010). Enhanced Bayesian foreground segmentation using brightness and color distortion region-based model for shadow removal. Proc. 17th IEEE International Conference on Image Processing IEEE 3449–3452.
Liu, Z., Zhao, F., Yang, H. (2010). A new method of moving shadow elimination combining texture and chrominance of moving foreground region based on criterion. Proc. 8th World Congress on Intelligent Control and Automation IEEE 6282–6286.
Porikli, F., Tuzel, O. (2005). Bayesian background modeling for foreground detection. Proc. the Third ACM International Workshop on Video Surveillance & Sensor Networks, ACM 55–58.
Doshi, A., Trivedi, M. (2006). Hybrid cone-cylinder codebook model for foreground detection with shadow and highlight suppression. Proc. IEEE International Conference on Video and Signal Based Surveillance IEEE 19–19.
Xu, C., Tian, Z., & Li, R. (2010). A fast motion detection method based on improved codebook model [J]. Journal of Computer Research and Development, 47(12), 2149–2156.
Amato, A., Mozerov, M. G., Bagdanov, A. D., & Gonzalez, J. (2011). Accurate moving cast shadow suppression based on local color constancy detection. IEEE Transactions on Image Processing, 20, 2954–2966.
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This work was supported in part by the Fundamental Research Funds for the Central Universities under Grant 2682014CX021 and the NSFC under Grant 61134002.
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Huang, J., Jin, W., Zhao, D. et al. Double-Trapezium Cylinder Codebook Model Based on YUV Color Model for Foreground Detection with Shadow and Highlight Suppression. J Sign Process Syst 85, 221–233 (2016). https://doi.org/10.1007/s11265-015-1068-3
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DOI: https://doi.org/10.1007/s11265-015-1068-3