结合图像增强和恢复的增强现实跟踪注册

doi:10.13474/j.cnki.11-2246.2020.0245

测绘通报 ›› 2020, Vol. 0 ›› Issue (8): 39-43,64.doi: 10.13474/j.cnki.11-2246.2020.0245

结合图像增强和恢复的增强现实跟踪注册

郭士祥¹, 范铀², 范冲¹

1. 中南大学地球科学与信息物理学院, 湖南长沙 410083;
2. 广东南方数码科技股份有限公司, 广东广州 510665

收稿日期:2020-04-03 发布日期:2020-09-01
通讯作者: 范冲。E-mail:68131632@qq.com E-mail:68131632@qq.com
作者简介:郭士祥(1994-),男,硕士生,研究方向为计算机视觉。E-mail:98719392@qq.com
基金资助:
国家重点研发计划（2018YFC0604405）

Augmented reality tracking registration combined with image enhancement and recovery

GUO Shixiang¹, FAN You², FAN Chong¹

1. School of Geosciences and Info-physics, Central South University, Changsha 410083, China;
2. South Digital Technology Co., Ltd., Guangzhou 510665, China

Received:2020-04-03 Published:2020-09-01

摘要/Abstract

摘要： 增强现实中的跟踪注册技术一直是研究的重点和难点，而地下矿道和巷道内亮度低，产生的图像较昏暗，车载相机快速运动和抖动，对传统的基于特征匹配的跟踪注册提出了挑战。本文从提高增强现实中跟踪注册稳健性和精度出发，采用基于Retinex改进的方法增强昏暗图像的亮度，同时利用基于对抗神经网络的方法恢复运动模糊图像。首先提取图像ORB特征，实现初始化；然后根据跟踪特征点的数量，开启图像增强和图像恢复线程，提高特征点提取质量和数量。在数据集和真实模拟场景下的试验结果显示，跟踪精度提高了12%左右，在低亮度和含有轻微模糊的情况下，跟踪注册稳健性也有显著提高。

关键词: 增强现实, 图像恢复, 图像增强, 特征检测, 跟踪注册

Abstract: Tracking registration technology in augmented reality has always been the focus and difficulty of research. However, the lowlight of underground mines and roadways resulting relatively dark image,and the on-board camera moving quickly and jitter,which challenge the traditional tracking registration based on feature matching. Starting from improving the robustness and accuracy of tracking registration in augmented reality, an improved method based on Retinex is used to enhance the brightness of dim images, and an adversarial neural network-based method is used to restore motion-blurred images. First, image ORB features is extracted to achieve initialization, and then the image enhancement and image restoration thread are started according to the number of tracked feature points to improve the quality and number of feature point extractions. Experimental results in the data sets and real simulation scenarios show that the tracking accuracy is improved by about 12%, and the robustness of tracking registration is also significantly improved in the case of low brightness and slight blur.

Key words: augmented reality, image restoration, image enhancement, feature detection, tracking registration

中图分类号:

P237

郭士祥, 范铀, 范冲. 结合图像增强和恢复的增强现实跟踪注册[J]. 测绘通报, 2020, 0(8): 39-43,64.

GUO Shixiang, FAN You, FAN Chong. Augmented reality tracking registration combined with image enhancement and recovery[J]. Bulletin of Surveying and Mapping, 2020, 0(8): 39-43,64.

参考文献

[1] BARSOM E Z, GRAAFLAND M, SCHIJVEN M P. Systematic review on the effectiveness of augmented reality applications in medical training[J].Surgical Endoscopy, 2016, 30(10):4174-4183.
[2] 徐剑坤, 杨乾龙, 杨乾霞, 等. 增强现实技术在采矿工程实验教学中的应用[J]. 实验室研究与探索, 2013, 32(2):136-139.
[3] 朱瑞军,李少辉,王磊.VR和AR及MR技术在矿山工程中的应用研究[J].中国矿山工程,2018,47(5):11-14.
[4] KANGSOO K, MARK B, GERD B, et al. Revisiting trends in augmented reality research:a review of the 2nd decade of ISMAR (2008-2017)[J]. IEEE Transactions on Visualization and Computer Graphics, 2018,24(11):2497-2962.
[5] RUBLEE E, RABAUD V, KONOLIGE K, et al. ORB:an efficient alternative to SIFT or SURF[C]//Proceedings of 2011 International Conference on Computer Vision.[S.l.]:IEEE, 2012.
[6] 侯守明, 韩吉, 张煜东, 等. 基于视觉的增强现实三维注册技术综述[J]. 系统仿真学报, 2019,31(11):2206-2215.
[7] MUR-ARTAL R, MONTIEL J M M, TARDOS J D. ORB-SLAM:a versatile and accurate monocular SLAM system[J]. IEEE Transactions on Robotics, 2015, 31(5):1147-1163.
[8] 张志禹, 刘耀阳. 基于SURF与光流法的增强现实跟踪注册[J].计算机工程与应用, 2015, 51(3):166-170.
[9] 雍玖, 王阳萍, 雷晓妹. 基于改进KCF的跟踪注册方法[J]. 计算机工程与科学, 2018,40(4):690-698.
[10] JOBSON D J, RAHMAN Z, WOODELL G A. A multiscale retinex for bridging the gap between color images and the human observation of scenes[J]. IEEE Transactions on Image Processing, 1997, 6(7):965-976.
[11] 李阳, 张路, 张志勇, 等. 一种改进的运动模糊图像恢复算法[J]. 计算机仿真, 2011, 28(5):254-257.
[12] KUPYN O, BUDZAN V, MYKHAILYCH M,et al. Deblur GAN:blind motion deblurring using conditional adversarial networks[C]//Proceedings of CVF Conference on Computer Vision and Pattern Recognition(CVPR).[S.l.]:IEEE, 2018.
[13] RUBLEE E, RABAUD V, KONOLIGE K, et al. ORB:an efficient alternative to SIFT or SURF[C]//Proceedings of 2011 International Conference on Computer Vision.[S.l.]:IEEE, 2012.
[14] KLEIN G, MURRAY D. Parallel tracking and mapping for small AR workspaces[C]//Proceedings of the 6th IEEE and ACM International Symposium on Mixed and Augmented Reality.[S.l.]:ACM, 2007.
[15] FU X, ZENG D, HUANG Y, et al. A fusion-based enhancing method for weakly illuminated images[J]. Signal Processing, 2016,129:82-96.
[16] BAHAT Y, EFRAT N, IRANI M. Non-uniform blind deblurring by reblurring[C]//Proceedings of 2017 IEEE International Conference on Computer Vision (ICCV).[S.l.]:IEEE, 2017.
[17] ZHU Z J, XU F,YAN C G, et al. Real-time indoor scene reconstruction with RGBD and inertial input[C]//Proceedings of 2019 IEEE International Conference On Multimedia and Expo (ICME).[S.l.]:IEEE, 2019.
[18] LI M, LIU J, YANG W, et al. Structure-revealing low-Light image enhancement via robust retinex model[J]. IEEE Transactions on Image Processing, 2018,27(6):2828-2841.
[19] ZHANG Z C, SCARAMUZZA D. A tutorial on quantitative trajectory evaluation for visual(-inertial) odometry[C]//Proceedings of 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).[S.l.]:IEEE,2018.

结合图像增强和恢复的增强现实跟踪注册

Augmented reality tracking registration combined with image enhancement and recovery

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