Abstract
In order to reduce crosstalk and support dynamic viewing, the mainstream autostereoscopic display technology requires high-precision three-dimensional eye localization. Due to the need of displaying high frame rate video images, higher requirements are put forward on the real-time performance of the three-dimensional eye localization algorithm. The three-dimensional measurement of the distance of the eye is particularly complicated, and stereo matching usually needs to be done with the help of binocular cameras. Aiming at the problem of low efficiency in conventional stereo matching, this paper improves and optimizes the ZNCC stereo matching algorithm from two aspects. On one hand, the operation logic of the matching algorithm is improved. It uses computer memory to save the intermediate results of the operation and uses a dynamic programming method to reduce the computational complexity of the matching cost function. On the other hand, the scanning strategy is optimized based on the application scenarios of stereoscopic display. Using the characteristics of the application scenarios and the additional constraints information of stereoscopic display, the search area is narrowed to reduce the frequency of the matching cost calculation. Various comparative experiments show that the method has the characteristics of strong real-time performance, strong robustness, and high accuracy, and can achieve great application effects in actual autostereoscopic display systems.
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References
Yuanqing, W.: Application and technology status of auto-stereoscopic display. Adv. Display. 01, 38–41 (2003)
Urey, H., et al.: State of the art in stereoscopic and autostereoscopic displays. Proc. IEEE 99(4), 540–555 (2011)
Yuanqing, W.: Research on the optical principle auto-stereo display base on grid. Adv. Display. 03, 29–32 (2003)
Woods, A.J.: Crosstalk in stereoscopic displays: a review. J. Electron. Imaging. 21(4), 0409 (2012)
Xicai, L., et al.: High-speed and robust infrared-guiding multiuser eye localization system for autostereoscopic display. Appl. Opt. 59(14), 4199–4208 (2020)
Brown, M.Z., Burschka, D., Hager, G.D.: Advances in computational stereo. IEEE Trans. Pattern Anal. Mach. Intell. 25(8), 993–1008 (2003)
Xicai, L., Qinqin, W., Yuanqing, W.: Binocular vision calibration method for a long-wavelength infrared camera and a visible spectrum camera with different resolutions. Opt Express. 29(3), 3855–3872 (2021)
Hamzah, R.A., Ibrahim, H.: Literature survey on stereo vision disparity map algorithms. J. Sensors 2016, 1–23 (2016)
Lazaros, N., Sirakoulis, G.C., Gasteratos, A.: Review of stereo vision algorithms: from software to hardware. Int. J. Optomechatron. 2(4), 435–462 (2008)
Yoo, J.-C., Han, T.H.: Fast normalized cross-correlation. Circ. Syst. Signal Process. 28(6), 819–843 (2009)
Briechle, K., Hanebeck, U.D.: Template matching using fast normalized cross correlation. In: Optical Pattern Recognition XII. International Society for Optics and Photonics, p. 4387 (2001)
Tsai, D.-M., Lin, C.-T.: Fast normalized cross correlation for defect detection. Pattern Recogn. Lett. 24(15), 2625–2631 (2003)
Wu, S., et al.: Funnel-structured cascade for multi-view face detection with alignment-awareness. Neurocomputing 221, 138–145 (2017)
Yan, S., et al.: Locally assembled binary (LAB) feature with feature-centric cascade for fast and accurate face detection. In: 2008 IEEE Conference on Computer Vision and Pattern Recognition. IEEE (2008)
Zhang, J., Shan, S., Kan, M., Chen, X.: Coarse-to-fine auto-encoder networks (cfan) for real-time face alignment. In: Fleet, David, Pajdla, Tomas, Schiele, Bernt, Tuytelaars, Tinne (eds.) ECCV 2014. LNCS, vol. 8690, pp. 1–16. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-10605-2_1
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Xiao, B., Ye, S., Li, X., Li, M., Zhang, L., Wang, Y. (2021). A Stereo Matching Method for Three-Dimensional Eye Localization of Autostereoscopic Display. In: Peng, Y., Hu, SM., Gabbouj, M., Zhou, K., Elad, M., Xu, K. (eds) Image and Graphics. ICIG 2021. Lecture Notes in Computer Science(), vol 12890. Springer, Cham. https://doi.org/10.1007/978-3-030-87361-5_3
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DOI: https://doi.org/10.1007/978-3-030-87361-5_3
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