Object tracking algorithm based on Bayes classification model and Haar-grey features on infrared camera
111 viewsDOI:
https://doi.org/10.54939/1859-1043.j.mst.92.2023.137-143Keywords:
Object tracking; Haar-grey features; Infrared object.Abstract
Object tracking based on thermal cameras is a core issue in security monitoring systems. During operation, the size and shape of the object can change continuously, especially thermal imaging objects with significant noise and blurred borders, making it difficult to capture and track. This article proposes a new algorithm based on the Haar-grey features of the object and the Bayesian classification model to track objects on the infrared image background. Experimental results show the effectiveness of the proposed algorithm.
References
[1]. Qu You-Shan, Fan Xue-Wu, Li Ying-Cai, Wen De-Sheng, Tian Wei-Jian, “Real-time detection of moving point targets in staring binocular imaging system”, Opto- Electronic Engineering, 33(1): 42-45, (2006). DOI: https://doi.org/10.1117/12.668038
[2]. Sun S G., “Target detection using local fuzzy thresholding and binary template matching in forward-looking infrared images”, Optical Engineering, 46(3), (2007). DOI: https://doi.org/10.1117/1.2714987
[3]. Li Long, Li Jun-Shan, Ye Xia, “Airborne infrared target tracking based on Mean Shift”, Infrared and Laser Engineering, 36(2): 229- 232, (2007).
[4]. Sun Ning, Wang Shou-Feng, Bai Jun-Qi, Zhao Chun-Guang, “A Real-Time Method for Infrared Target Tracking”, Electronics Optics & Control, 19(10): 25- 29, (2012).
[5]. Gupta U, Dutta M, Vadhavaniya M., “Analysis of Target Tracking Algorithm in Thermal Imagery”, International Journal of Computer Applications, 71 (16): 34- 41, (2013). DOI: https://doi.org/10.5120/12443-9140
[6]. Ling Jian-Guo, Liu Er-Qi, Liang Hai-Yan, Yang Jie, “Infrared target tracking method based on regularized observation vector H infinity particle filter”, Infrared and Laser Engineering, 36(4): 534- 538, (2007).
[7]. Li Z, Chen J, Gu Y, Tang L, Dai Z, Fu H., “Small moving infrared space target tracking algorithm based on probabilistic data association filter”, Infrared Physics & Technology, 2014, 63(2): 84-91. DOI: https://doi.org/10.1016/j.infrared.2013.12.003
[8]. Li X L and Askar H., “Infrared dim-small target tracking algorithm based on local similarity”, Laser and Infrared, 51(5): 668-674, (2021).
[9]. Wang L, Ouyang W, Wang X, Lu H., “Visual Tracking with Fully Convolutional Networks”, In: Proceedings of the IEEE International Conference on Computer Vision, 3119-3127, (2015). DOI: https://doi.org/10.1109/ICCV.2015.357
[10]. Ma C, Huang J B, Yang X, Yang M H., “Hierarchical Convolutional Features for Visual Tracking”, Pro. of the IEEE International Conference on Computer Vision, 3074-3082, (2015). DOI: https://doi.org/10.1109/ICCV.2015.352
[11]. Zhang K, Liu Q, Wu Y, Yang M H., “Robust Visual Tracking via Convolutional Networks Without Training”, IEEE Transactions on Image Processing, 25(4): 1779-1792, (2016).
[12]. Ji Q B, Chen K C., “Infrared target tracking algorithm based on attention mechanism enhancement and target model update”, Journal of Image and Graphics, 28(9): 2856-2871, (2023). DOI: https://doi.org/10.11834/jig.220459
[13]. Zhang K, Zhang L, Yang M H., “Fast Compressive Tracking”, IEEE Transactions on Pattern Analysis & Machine Intelligence, 36(10): 2002- 2015, (2014). DOI: https://doi.org/10.1109/TPAMI.2014.2315808
[14]. Diaconis P, Freedman D., “Asymptotics of Graphical Projection Pursuit”, Annals of Statistics, 12(3): 793-815, (1984). DOI: https://doi.org/10.1214/aos/1176346703
[15]. Felsberg M, Berg A, Hager G, et al, “The Thermal Infrared Visual Object Tracking VOT-TIR2015 Challenge Results”, In: Proceedings of the IEEE International Conference on Computer Vision Workshops, 76- 88, (2015).
[16]. Wang N, Yeung D Y., “Learning a deep compact image representation for visual tracking”, Advances in Neural Information Processing Systems, 809-817, (2013).
[17]. Xue L, Wang Z. Chen Y., “Multi-target Tracking Algorithm Based on TLD under Dynamic Background”, International Journal of Hybrid Information Technology, 8(7): 267- 276, (2015). DOI: https://doi.org/10.14257/ijhit.2015.8.7.25
