進化的最適化によるリアルタイムレンダリングベースの手術器具追跡
Real-time Rendering-based Surgical Instrument Tracking via Evolutionary Optimization
CMA-ES進化戦略とバッチレンダリングを組み合わせ、手術器具の位置・関節構成を高速かつロバストに推定する追跡手法を提案。合成・実データで精度と速度を大幅に向上した。
詳しい要約
1. どんなもの？
2. 先行研究と比べてどこがすごい？
3. 技術・手法の肝は？
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著者: Hanyang Hu, Zekai Liang, Florian Richter, Michael C. Yip
分類: cs.RO, cs.CV
原文アブストラクト
Accurate and efficient tracking of surgical instruments is fundamental for Robot-Assisted Minimally Invasive Surgery. Although vision-based robot pose estimation has enabled markerless calibration without tedious physical setups, reliable tool tracking for surgical robots still remains challenging due to partial visibility and specialized articulation design of surgical instruments. Previous works in the field are usually prone to unreliable feature detections under degraded visual quality and data scarcity, whereas rendering-based methods often struggle with computational costs and suboptimal convergence. In this work, we incorporate CMA-ES, an evolutionary optimization strategy, into a versatile tracking pipeline that jointly estimates surgical instrument pose and joint configurations. Using batch rendering to efficiently evaluate multiple pose candidates in parallel, the method significantly reduces inference time and improves convergence robustness. The proposed framework further generalizes to joint angle-free and bi-manual tracking settings, making it suitable for both vision feedback control and online surgery video calibration. Extensive experiments on synthetic and real-world datasets demonstrate that the proposed method significantly outperforms prior approaches in both accuracy and runtime. Source code and data are available at https://github.com/hanyang-hu/online_dvrk_tracking.
関連論文
- 画素確率に基づく投影幾何プリミティブを用いたロバストな手術器具トラッキング手術ロボット/トラッキング
