标题: 利用智慧眼镜及电脑视觉技术作户外街景之即时扩增实境式导览
A Real-time Mobile Augmented-reality System for Street-area Exploration by Computer Vision Techniques Using Smart Glasses
作者: 柯婷文
蔡文祥
Ko, Ting-Wen
Tsai, Wen-Hsiang
资讯科学与工程研究所
关键字: 扩增实境;智慧眼镜;影像辨识;定向定位;电脑视觉;augmented reality;smart glasses;image recognization;human localization;computer vision
公开日期: 2016
摘要: 当人们到户外旅游时,常会有迷路或不知如何到达想去地点或建筑物的情形,而近年来发展之导航系统虽可解决部分问题,但不能普遍应用于各种户外街景,且对使用者来说,仍不够直觉。对此,本研究提出一个利用电脑视觉技术与智慧型眼镜,应用于户外旅游场所的即时扩增实境式导览系统。所提系统事先建立一导览地图,提供游客旅游资讯,并有两个主要功能:旅游导览及建筑物资讯介绍,皆是建立在扩增实境的技术上。此系统可以指引游客到事先选取的建筑物,以及将建筑物资讯扩增到使用者所戴智慧型眼镜的萤幕上。
为了完成上述功能,所提系统首先建立一环境地图,包含旅游路线区域平面图及沿线建筑物资讯;对此,本研究提出一个建立地图资料库之应用程式,以智慧型眼镜的相机拍摄整段路线上建筑物的影像,并记录其对应位置;之后将所有资料储存至一资料库,供进行导览时使用。
接下来,本研究提出一个利用加速稳健特征(SURFs)做影像辨识的演算法,来对使用者进行定位的方法。该方法首先要求使用者对邻近建筑物拍摄影像,接着利用加速稳健特征,将建筑物影像与事先建立的影像资料库做比对,进行建筑物辨识。接着,本研究提出三个过滤不佳比对之演算法,用以提升辨识率。最后,根据使用者拍摄的影像与建筑物辨识结果之间的透视关系,完成使用者定位,获得使用者位置及方向参数。
此外,本研究提出三个加速系统之方法,达成即时导览的作用。最后,本研究提出一扩增实境式导览与建筑物资讯介绍的方法。对此,所提系统会根据使用者的位置及方向参数,利用戴克斯特拉(Dijkstra)演算法,规划一条从使用者位置到一事先选取的目的地之间的最短路径,并在智慧型眼镜萤幕中的沿路影像上贴上一扩增实境式箭头,来指引使用者该往哪里走。此外,也在智慧型眼镜萤幕上扩增眼前所见建筑物之名称,以及建筑物相关资讯,供使用者观看。
最后,本研究实验结果良好,足以证明所提系统确实可行。
In this study, a realtime augmented reality (AR)-based tour guidance system for outdoor street-area exploration has been proposed. The system is based on computer vision techniques for uses while visiting outdoor street areas. It solves a tourist’s problem of getting lost in unfamiliar streets, having no idea about reaching a desired location, or even being unable to comprehend a map of the area. The system has the following functions. Firstly, a simple way to learn the street-area environment before touring is provided. Secondly, accurate user positions and orientations are computed. Thirdly, the latest user position and orientation are updated in a realtime fashion so that the user can always know where he/she is at any moment. Fourthly, a proper and shortest guidance path is planned to guide the user and update an augmented guidance arrow shown on the display of a pair of smart glasses dynamically when the user is walking toward a wrong direction. Finally, the information about the traversed or visited buildings is displayed on the device in an AR manner, by which the user can get more knowledge about the buildings.
To implement such a system, at first an environment map is generated in the learning phase, which includes a top-view map of the selected tour paths and the information about the along-path buildings. In addition, the images of the buildings taken by the camera of the smart glasses and the corresponding building locations along the entire tour path are also learned. All the learned data are saved into a database for use in the guidance phase.
Next, a method for user localization is proposed, which is based on image matching using speeded up robust features (SURFs). At first, the server-side of the system receives the image taken by the camera of the smart glasses. Secondly, image matching is conducted against the pre-constructed image database by an SURF matching algorithm. Then, three methods of speeding up the feature-matching work are applied. Finally, user localization is conducted by the system to obtain the user’s position and orientation parameters according to the perspective relationship between the image taken by the user and the matching result.
Furthermore, to realize realtime guidance, methods of speeding up images transmission and image processing are also proposed for use both in the learning phase and in the guidance phase, so that the AR information and guidance arrow can be updated and displayed on the screen of the smart device in realtime. Finally, a method for AR-based guidance and building-information introduction is proposed. Based on the user’s position and orientation, a shortest path from the user’s location to the pre-selected destination is planned by use of the Dijkstra algorithm. Accordingly, an AR-based arrow is rendered and augmented on the acquired along-path scene image on the screen to guide the user where to go. Also augmented on the screen is the information of the building according to the user localization result.
Good experimental results are also presented to show the feasibility of the proposed methods and the system for real applications.
URI: http://etd.lib.nctu.edu.tw/cdrfb3/record/nctu/#GT070456012
http://hdl.handle.net/11536/143250
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