Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4947210 | Neurocomputing | 2017 | 18 Pages |
Abstract
With the development of computer vision in recent year, 3D models have been utilized in many applications, such as virtual reality, medical surgical, geographic information system. With the growth of 3D models, it is necessary to develop effective 3D model retrieval methods for data management. In this paper, we proposed a novel algorithm based on multimodal 3D model data to handle model retrieval problem. First, we extract structure information and visual information from each virtual 3D model. Then, a universal graph matching is employed to handle similarity measure in different modals respectively. Finally, a simple statistical model is utilized to handle similarity measure and finish retrieval process. The final comparing experiments demonstrate the superiority of our approach.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Anan Liu, Wenhui Li, Weizhi Nie, Yuting Su,