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Object recognition via multi-view inspection using saturation-weighted distributive hue histograms and depth information

机译:通过使用饱和度加权分布色相直方图和深度信息的多视图检测进行对象识别

摘要

A computer vision algorithm is presented for the detection and localization of objects within unknown environments. To search for a specific object within an image, information about the objectu27s appearance is first extracted from database images of the object. To effectively represent the appearance of the object, the Saturation-Weighted Distributive Hue Histogram is presented which encapsulates the intrinsic color information of the object as well as the spatial arrangement of colors within the objectu27s boundaries. These histograms are then searched for in the scene image of the environment. The use of depth information allows searching for objects at depth variant planes in order to achieve scale invariance and to obtain the 3D coordinates of match candidates. A mobile robot platform is employed to move to various locations within the environment and to inspect matching regions by capturing and processing further images.
机译:提出了一种计算机视觉算法,用于检测和定位未知环境中的对象。为了在图像中搜索特定对象,首先要从对象的数据库图像中提取有关该对象外观的信息。为了有效地表示对象的外观,提出了饱和度加权分布色相直方图,该直方图封装了对象的固有颜色信息以及对象边界内颜色的空间排列。然后在环境的场景图像中搜索这些直方图。深度信息的使用允许在深度变体平面上搜索对象,以实现尺度不变性并获得匹配候选者的3D坐标。使用移动机器人平台来移动到环境中的各个位置,并通过捕获和处理其他图像来检查匹配区域。

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    Westell Jamie;

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  • 年度 2010
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