DynamicPose：高速移動するカメラと物体のためのリアルタイムで堅牢な6D物体姿勢追跡
DynamicPose: Real-time and Robust 6D Object Pose Tracking for Fast-Moving Cameras and Objects
カメラと物体が同時に高速移動する場面でも、視覚慣性オドメトリと深度情報を活用した2Dトラッカー、カルマンフィルタを組み合わせ、再学習なしでリアルタイムに6D姿勢を追跡するフレームワークを提案した。
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著者: Tingbang Liang, Yixin Zeng, Jiatong Xie, Boyu Zhou
分類: cs.CV, cs.RO
原文アブストラクト
We present DynamicPose, a retraining-free 6D pose tracking framework that improves tracking robustness in fast-moving camera and object scenarios. Previous work is mainly applicable to static or quasi-static scenes, and its performance significantly deteriorates when both the object and the camera move rapidly. To overcome these challenges, we propose three synergistic components: (1) A visual-inertial odometry compensates for the shift in the Region of Interest (ROI) caused by camera motion; (2) A depth-informed 2D tracker corrects ROI deviations caused by large object translation; (3) A VIO-guided Kalman filter predicts object rotation, generates multiple candidate poses, and then obtains the final pose by hierarchical refinement. The 6D pose tracking results guide subsequent 2D tracking and Kalman filter updates, forming a closed-loop system that ensures accurate pose initialization and precise pose tracking. Simulation and real-world experiments demonstrate the effectiveness of our method, achieving real-time and robust 6D pose tracking for fast-moving cameras and objects.
