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Image Texts-Based Navigation for Augmented Game

机译:基于图像文本的增强游戏导航

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摘要

In an augmented game is a game, which is overlapping virtual objects on a real environment and attacking the virtual objects, accurate location estimation in a real environment is one of important issues. Existing global positioning systems(GPS) to track users' positions do not work inside a building, and systems using sensors such as Active Badge are expensive to install and maintain. Therefore, researches for low-cost vision-based navigation system have been attempted. Since most of scenes include a floor, ceiling and wall in a building, it is difficult to represent characteristics of those scenes. We propose an image matching method using image texts instead of objects included uniformly in natural scenes for navigation. The image texts are widely distributed in our environments, are very useful for describing the contents of an image, and can be sassily extracted compared to other semantic contents, and we obtain image texts using a method combining edge density and multi-layer perceptrons with CAMShift. However, since a camera attached to moving vehicles(robots) or hand-held devices has a low resolution, it is not easy to perform extraction using a binarization and a text recognition. Therefore, we perform an image matching using a matching window based on a scale and orientation of image texts and its neighborhood to recognize discriminated places including same image texts.
机译:在增强型游戏中,是在真实环境中重叠虚拟对象并攻击虚拟对象的游戏,在真实环境中进行准确的位置估计是重要的问题之一。现有的用于跟踪用户位置的全球定位系统(GPS)在建筑物内不起作用,并且使用诸如Active Badge之类的传感器的系统的安装和维护成本很高。因此,尝试了低成本的基于视觉的导航系统的研究。由于大多数场景包括建筑物中的地板,天花板和墙壁,因此很难表示这些场景的特征。我们提出一种图像匹配方法,该方法使用图像文本代替自然场景中统一包含的对象进行导航。图像文本在我们的环境中分布广泛,对于描述图像的内容非常有用,并且与其他语义内容相比可以轻松提取,并且我们使用结合了边缘密度和多层感知器以及CAMShift的方法来获得图像文本。 。但是,由于安装在移动的车辆(机器人)或手持设备上的相机分辨率较低,因此使用二值化和文本识别进行提取并不容易。因此,我们使用基于图像文本及其附近的比例和方向的匹配窗口来执行图像匹配,以识别包括相同图像文本的辨别位置。

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