In refractive cataract surgery, precise alignment of the toric intraocular lens with the intended axis of astigmatism is critical, but challenges arise due to intraoperative eye rotation. While existing computer-assisted navigation methods primarily address first-frame rotation in the microscopic video, they neglect significant intraoperative rotation among video frames, termed as inter-frame rotation. In this study, we propose a novel inter-frame rotation computation pipeline leveraging sclera vessel features, which involves extracting and normalizing sclera regions of a reference and intraoperative microscopic video frame into polar representations, recognizing prominent feature points to initialize a multi-regions of interests (ROIs) correlation rotation tracker, and computing the rotation degree to update the alignment axis in toric intraocular lens (IOL) implantation navigation. Ablation experimental results validate the effectiveness of each component in the proposed pipeline, and comparative experiments highlight the pipeline’s superior performance over related methods. Crucially, we seamlessly integrate this rotation pipeline into an augmented reality navigation system for cataract surgery, with preliminary validation demonstrating its effectiveness in a real clinical setting.