Aiming at the problem of low efficiency of tampering detection and accuracy of location, a homologous video copy-move tampering detection and recovering method based on Geometric Mean Decomposition (GMD) and Structural SIMilarity (SSIM) was proposed. Firstly, the videos were translated into grayscale image sequences. Then, the geometric mean decomposition was adopted as a feature and a block-based search strategy was put forward to locate the starting frame of the duplicated sequences. In addition, SSIM was first extended to measure the similarity between two frames of a video. The starting frame of duplicated sequences was rechecked by using the structural similarity. Since the value of similarity between duplicated frames is higher than that between the normal inter-frames, a coarse-to-fine method based on SSIM was put forward to locate the tail frame. Finally, the video was recovered. In comparison with other classical algorithms, the experimental results show that the proposed method can not only achieve detection of copy-move forgery but also accurately detect and localize duplicated clips in different kinds of videos. Besides, the method has a great improvement in terms of precision, recall and computation time.