In this paper, a vision-based video synchronization method was developed based on feature point matching. The proposed method contains several parts: pre-processing, key-frame matching, and frame synchronization. Since videos may have different frame rates and frame sizes, the pre-processing procedure is used to normalize the frame rate and frame size of videos. After key frame extraction, matching similar key frames from difference videos is conducted based on feature point matching and RANSAC. The frame index differences among videos can be obtained by analyzing these matched key frames and then synchronizing videos can be achieved. To evaluate the performance of the proposed method, some videos are captured for testing. Experimental results show that key frames can be selected effectively. Frame matching can be well achieved based on feature point matching and RANSAC. The higher score of subjective testing demonstrates that the proposed system can synchronize videos well.