Abstract
If a certain group of people have been gathered in public places, in the event of an accident, the loss may be huge. Nowadays, there are more and more emergencies in some crowded public places such as scenic spots. The difficulty of monitoring is gradually increasing, and the need for monitoring is gradually emphasized. In the current situation, most video surveillance systems only replace the human eye to record the results as the basis for handling accidents. Therefore, they cannot detect potential actual hazards in time, and cannot perform real-time functions to actively analyze and monitor. This article mainly introduces the research of garden visitor detection based on the improved ViBe algorithm, and intends to provide ideas and directions for the improvement of garden visitor detection technology. This paper proposes an improved ViBe algorithm, including fixed threshold improvement and ghost elimination methods to improve the problems in traditional ViBe. The experimental results of this paper show that the average accuracy of the garden visitor detection method designed in this paper is 93.78%, which fully demonstrates the superiority of the improved ViBe algorithm.
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References
Zhang, Q., Lu, W., Huang, C., et al.: An adaptive vibe algorithm based on dispersion coefficient and spatial consistency factor. Autom. Control Comput. Sci. 54(1), 80–88 (2020)
Min, W., Fan, M., Guo, X., et al.: A new approach to track multiple vehicles with the combination of robust detection and two classifiers. IEEE Trans. Intell. Transp. Syst. 19(1), 174–186 (2017)
Zhou, F., Pan, S., Jiang, J.: Verification of AIS data by using video images taken by a UAV. J. Navig. 72(6), 1–14 (2019)
Jiang, K., Wang, J.: Research on improved adaptive ViBe algorithm for vehicle detection. Int. J. Adv. Netw. Monit. Controls 4(4), 11–17 (2019)
Cai, N., Lin, J., Ye, Q., et al.: A new IC solder joint inspection method for an automatic optical inspection system based on an improved visual background extraction algorithm. IEEE Trans. Compon. Packag. Manuf. Technol. 6(1), 161–172 (2017)
Zhao, L.L., Chen, Y., Zou, Y., et al.: Shooting for smarter motion detection in cameras: improvements for the visual background extractor algorithm using optical flow. IEEE Consum. Electron. Mag. 6(4), 81–91 (2017)
Sun, N., Shan, Y., Jiang, F., et al.: An ensemble framework for object detection in intelligent video surveillance system. Int. J. Control Autom. 9(2), 239–248 (2016)
Apraites, L., Atlas, A., Karami, F., et al.: Some class of parabolic systems applied to image processing. Discret. Continuous Dyn. Syst. – Ser. B (DCDS-B) 21(6), 1671–1687 (2017)
Kamel, I.R., Georgiades, C., Fishman, E.K.: Incremental value of advanced image processing of multislice computed tomography data in the evaluation of hypervascular liver lesions. J. Comput. Assist. Tomogr. 27(4), 652–656 (2017)
Bresson, X., Chan, T.F., Chan, T.F.C.: Fast dual minimization of the vectorial total variation norm and applications to color image processing. Inverse Probl. Imaging 2(4), 455–484 (2017)
Matsumoto, T., Mizuuchi, Y., Furuya, K.: A study on grasp of utilization form in Koishikawa Korakuen by using visitor employed photography and spatial information technology. J. Japan. Inst. Landscape Architect. 79(5), 477–482 (2016)
Martin, R.D., Yohai, V.J.: 4 Robustness in time series and estimating ARMA models. Handb. Stat. 5(85), 119–155 (2016)
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Shu, Z. (2021). Garden Visitor Detection Based on Improved Vibe Algorithm. In: Sugumaran, V., Xu, Z., Zhou, H. (eds) Application of Intelligent Systems in Multi-modal Information Analytics. MMIA 2021. Advances in Intelligent Systems and Computing, vol 1385. Springer, Cham. https://doi.org/10.1007/978-3-030-74814-2_14
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DOI: https://doi.org/10.1007/978-3-030-74814-2_14
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