A portable real-time scene recognition system on smartphone

Zhenwen Gui
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Abstract

In the context of mapping and mobile navigation services, the recognition of the urban infrastructure plays an important role. However, majority of the existing recognition methods cannot be effectively run on the smartphones due to their large computational costs and high storages. In this paper, a fast scene recognition approach is introduced by fusing the outputs of inertial sensors and cameras of smartphones for real-time applications in large scenes. The proposed algorithm possesses the virtues of implementation easiness, storage efficiency and computation significance. Experimental results on the datasets of outdoor scenes and UKBench datasets demonstrate the effectiveness and robustness of the proposed algorithm.
基于智能手机的便携式实时场景识别系统
在地图和移动导航服务的背景下,城市基础设施的识别起着重要的作用。然而,现有的大多数识别方法由于其庞大的计算成本和高存储而无法在智能手机上有效运行。本文介绍了一种融合惯性传感器和智能手机摄像头输出的快速场景识别方法,用于大场景下的实时应用。该算法具有实现简单、存储效率高、计算量大等优点。在室外场景数据集和UKBench数据集上的实验结果表明了该算法的有效性和鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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