In anterior and posterior cruciate ligament (ACL and PCL) reconstructions, the intraoperative joint condition is different from preoperative CT due to the knee flexion applied during surgery. This study aims to provide non-invasive augmented reality (AR)-based surgical guidance for ACL and PCL reconstruction using the correlation model between knee surface and internal bones (femur and tibia). First, We defined individual finite element models for the knee surface, femur, and tibia. The correlation model is implemented by introducing mapping between finite element models. The internal bones move according to the shape deformation of the knee surface using the correlation model. Finally, registration between the depth data of the knee surface and the correlation model is performed to visualize AR. The magnitude of constraint forces is determined based on the registration result to deform the correlation model. The proposed method was evaluated with the flexion state knee CT and demonstrated successful AR compensating the knee movements.