surface_matching

最新推荐文章于 2024-04-09 23:52:44 发布

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最新推荐文章于 2024-04-09 23:52:44 发布 · 1.3k 阅读

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本文提出了一种结合强度和深度数据的3D对象检测和定位方案，使用新颖的多模态、尺度和旋转不变特征来描述物体轮廓和表面外观。通过局部投票匹配场景和模型特征确定物体位置。实验证明，该方法对遮挡和杂乱环境具有高度鲁棒性，并与现有方法相比具有更好的表现。

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3D Object Detection and Localization using Multimodal Point Pair Features

abstract

Object detection and localization is a crucial step for inspection and manipulation tasks in robotic and industrial applications. We present an object detection and localization scheme for 3D objects that combines intensity
and depth data. A novel multimodal, scale- and rotation- invariant feature is used to simultaneously describe the object’s silhouette and surface appearance. The object’s position is determined by matching scene and model features via a Hough-like local voting scheme. The proposed method is quantitatively and qualitatively evaluated on a large number of real sequences, proving that it is generic and highly robust to occlusions and clutter. Comparisons with state of
the art methods demonstrate comparable results and higher robustness with respect to occlusions.<