Abstract

Visual tracking is an essential process for performing automated cell manipulation tasks. However, Real-time accurate cell tracking in FluidFM is challenging due to probe occlusion during manipulation. This study presents a correlation filtering-based tracking method for real-time, high-precision position tracking of cells and probes. In this method, a target template update strategy is proposed to realize cell tracking under probe occlusion, which abandons the use of pixel values in the occlusion area and reduces the interference of the occlusion area in model learning. Cell tracking and automated manipulation experiments were carried out to validate the proposed method. The Experimental results show that the proposed tracking method can accurately measure the positions of occlusion cells and probe. Furthermore, combined with the precise force control of the FluidFM’s probe, the automated cell Pick & Place experiments was accomplished with high accuracy and robustness.

摘要

视觉跟踪是执行自动化细胞操作任务的基本过程。然而，由于操作过程中的探针遮挡，FluidFM 中的实时准确细胞跟踪具有挑战性。本研究提出了一种基于相关滤波的跟踪方法，用于对细胞和探针进行实时、高精度的位置跟踪。该方法提出了目标模板更新策略实现探针遮挡下的细胞跟踪，摒弃了遮挡区域像素值的使用，减少了遮挡区域对模型学习的干扰。进行细胞跟踪和自动操作实验以验证所提出的方法。实验结果表明，所提出的跟踪方法可以准确测量遮挡细胞和探针的位置。此外，