移動ロボットナビゲーションにおける物体検出維持のための物体らしさスコア
An Objectness Score for Accurate and Fast Detection during Navigation
移動ロボットがナビゲーション中にMask R-CNNで検出した物体の位置とクラスを維持するため、カメラとの距離に応じて変化する物体らしさスコアを提案し、角度や距離が変わっても効率的かつ頑健に追跡できることを示した。
著者: Hongsun Choi, Mincheul Kang, Youngsun Kwon, Sung-eui Yoon
分類: cs.CV, cs.RO
原文アブストラクト
We propose a novel method utilizing an objectness score for maintaining the locations and classes of objects detected from Mask R-CNN during mobile robot navigation. The objectness score is defined to measure how well the detector identifies the locations and classes of objects during navigation. Specifically, it is designed to increase when there is sufficient distance between a detected object and the camera. During the navigation process, we transform the locations of objects in 3D world coordinates into 2D image coordinates through an affine projection and decide whether to retain the classes of detected objects using the objectness score. We conducted experiments to determine how well the locations and classes of detected objects are maintained at various angles and positions. Experimental results showed that our approach is efficient and robust, regardless of changing angles and distances.
