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点群レジストレーションarXiv:1709.05945

複数手がかりを統合する汎用フォトメトリック点群レジストレーション

A General Framework for Flexible Multi-Cue Photometric Point Cloud Registration

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色・深度・法線などの複数モダリティを統一的に扱い、画素ごとの差分最小化で点群を位置合わせする汎用フレームワークを提案し、RGBDや3D LiDARで有効性を示した。

著者: Bartolomeo Della Corte, Igor Bogoslavskyi, Cyrill Stachniss, Giorgio Grisetti

分類: cs.CV, cs.RO

原文アブストラクト

The ability to build maps is a key functionality for the majority of mobile robots. A central ingredient to most mapping systems is the registration or alignment of the recorded sensor data. In this paper, we present a general methodology for photometric registration that can deal with multiple different cues. We provide examples for registering RGBD as well as 3D LIDAR data. In contrast to popular point cloud registration approaches such as ICP our method does not rely on explicit data association and exploits multiple modalities such as raw range and image data streams. Color, depth, and normal information are handled in an uniform manner and the registration is obtained by minimizing the pixel-wise difference between two multi-channel images. We developed a flexible and general framework and implemented our approach inside that framework. We also released our implementation as open source C++ code. The experiments show that our approach allows for an accurate registration of the sensor data without requiring an explicit data association or model-specific adaptations to datasets or sensors. Our approach exploits the different cues in a natural and consistent way and the registration can be done at framerate for a typical range or imaging sensor.

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