Image data and 3D model data have emerged as resourceful foundation for information with proliferation of image capturing devices and social media. In this paper, a feature matching method based on hash binary encoding for multi-view 3D models in social media is proposed. SIFT algorithm is first used to extract features of the depth image, and then RANSAC is utilized as a filter. Finally, a cascade hash binary encoding algorithm is adapted to match the feature of multi-view models. Experimental results on SHREC2014 dataset have shown the effectiveness of the proposed method.