基于增强现实与情境感知图像识别的离线麻将支持系统

Ryosuke Suzuki, Tadachika Ozono, T. Shintani
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引用次数: 0

摘要

增强现实框架的推广促进了对现实世界任务的支持系统的实施。本文介绍了一个支持初学者麻将游戏的系统。然而,在真正的麻将游戏中,初学者很难计算分数。我们开发了一个离线系统,通过识别麻将牌来获得分数。这是一项艰巨的任务,因为麻将有类和属性,这是他们的位置的上下文。该系统需要上下文感知图像识别。该系统利用OpenCV和卷积神经网络对瓷砖进行分类,并在属性中间接找到自定位。实验结果表明,该系统可以有效地应用。
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An Offline Mahjong Support System Based on Augmented Reality with Context-aware Image Recognition
The diffusion of the Augmented Reality framework has facilitated the implementation of a support system for a real world task. This paper introduces a system that supports the Mahjong game for beginners. However, it is difficult to calculate the score for beginners in the real Mahjong game. We develop an offline system to get the score by recognizing the Mahjong tiles. This is a difficult task because Mahjong tiles have classes and attributes that are the context of their positions. The system needs context-aware image recognition. The system detected tiles using OpenCV and Convolutional Neural Network to classify them and self-localization indirectly found in attributes. The experimental results show that the system can be used effectively.
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