非構造環境におけるキーポイントパッチの設計と識別
Design and Identification of Keypoint Patches in Unstructured Environments
雑然とした環境でも頑健に検出できる4種類のキーポイントパッチを設計し、Superpointネットワークを改良して実映像で有効性を示した研究。
著者: Taewook Park, Seunghwan Kim, Hyondong Oh
分類: cs.RO, cs.CV
原文アブストラクト
Reliable perception of targets is crucial for the stable operation of autonomous robots. A widely preferred method is keypoint identification in an image, as it allows direct mapping from raw images to 2D coordinates, facilitating integration with other algorithms like localization and path planning. In this study, we closely examine the design and identification of keypoint patches in cluttered environments, where factors such as blur and shadows can hinder detection. We propose four simple yet distinct designs that consider various scale, rotation and camera projection using a limited number of pixels. Additionally, we customize the Superpoint network to ensure robust detection under various types of image degradation. The effectiveness of our approach is demonstrated through real-world video tests, highlighting potential for vision-based autonomous systems.
