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Terrain Classification from Body-mounted Cameras during Human Locomotion

机译:人体运动过程中车载摄像头的地形分类

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摘要

This paper presents a novel algorithm for terrain type classification based on monocular video captured from the viewpoint of human locomotion. A texture-based algorithm is developed to classify the path ahead into multiple groups that can be used to support terrain classification. Gait is taken into account in two ways. Firstly, for key frame selection, when regions with homogeneous texture characteristics are updated, the frequency variations of the textured surface are analysed and used to adaptively define filter coefficients. Secondly, it is incorporated in the parameter estimation process where probabilities of path consistency are employed to improve terrain-type estimation. When tested with multiple classes that directly affect mobility a hard surface, a soft surface and an unwalkable area - our proposed method outperforms existing methods by up to 16%, and also provides improved robustness.
机译:本文从人类运动的角度提出了一种基于单眼视频的地形类型分类新算法。开发了基于纹理的算法,将前方的路径分类为可用于支持地形分类的多个组。步态有两种考虑方式。首先,对于关键帧选择,当更新具有均匀纹理特征的区域时,分析纹理表面的频率变化并用于自适应地定义滤波器系数。其次,将其合并到参数估计过程中,其中使用路径一致性的概率来改善地形类型估计。当使用直接影响活动性的多个类别进行测试时,硬表面,软表面和无法行走的区域-我们提出的方法比现有方法的性能高出16%,并且还提供了改进的耐用性。

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