高度动态的微创手术环境下，如何实时、准确的恢复在体软组织表面三维形态并估计其运动，是机器人辅助微创手术系统未来智能化发展的瓶颈问题。立体内窥镜的出现为应用被动视觉跟踪技术解决该问题提供了良机，但多数已有的视觉跟踪方法并不适用于动态的手术环境和复杂的软组织形变。本项目致力于探索高效、鲁棒的软组织运动三维视觉跟踪方法。拟采用统计形状和生物力学模型描述软组织三维形变；应用与呼吸和心动周期相关的准周期信号对软组织时间运动建模。拟应用在线学习和多分辨率分析技术提取组织表面的可辨识特征。在特征空间，基于形变和运动模型将三维重构和运动估计描述为统一的数学问题并探究其快速求解。研究应对术中典型动态干扰的鲁棒性方法。探索无真值情况下跟踪结果的定量评价问题，尝试建立标准测试集。本项目是对复杂环境下非刚性形变目标视觉跟踪的最新拓展和深化，预期成果可提升手术机器人现有能力，具有较高的科学意义和重要的临床应用价值。

Real-time and accurate 3D reconstruction and motion estimation of in vivo soft-tissue surface, in a highly dynamic Minimally Invasive Surgery (MIS) setting, is a bottleneck for the further intelligentized development of robotic-assisted MIS. The advent of stereo-endoscope provides a unique opportunity to solve the problem using non-invasive visual tracking techniques. However, most existing visual tracking methods do not apply to the dynamic surgical environment and complex tissue deformation. This proposed study aims to explore efficient and robust methods for 3D visual tracking of soft-tissue motion. Statistical shape and biomechanical models will be used to represent the spatial shape of soft-tissue. The temporal motion of soft-tissue may be modeled by a quasi-periodic signal that relates to cardiac and respiratory periodic motions. Online learning and multi-resolution analysis techniques will be introduced to extract discriminate features on tissue surface. In feature space, the 3D reconstruction and motion estimation will be formulated as an integrated mathematical problem based on the deformation and motion models, and its fast solution algorithm will be studied. Robust techniques are investigated to deal with typical dynamic disturbances in MIS. Quantitative methods will be explored to evaluate the tracked results with absence of ground truth, and it is expected to establish a benchmark data set for algorithm evaluation. The proposed work presents as a novel expansion and deeper understanding of nonrigid deformable object tracking in a complex scenario, and the expected achievements will boost current capability of surgical robots. Thus the proposed work possesses high scientific significance and particular clinical value.