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A unified framework for cross-modality 3D model retrieval

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Abstract

Currently, there exists diverse modalities of 3D models, such as the view set representation of 3D models, the virtual 3D model designed by CAD tools, and the 2.5D model captured by Kinect sensors. To realize flexible access to 3D models in different modalities, this paper proposes the unified framework for cross-modality 3D model retrieval. First, we develop a toolbox with OpenGL to convert 3D models in multiple modalities into the view set representation of 3D models, which are usually represented by a set of characteristic views. Then, we extract discriminative visual feature for multi-view representation. These visual features can be utilized to construct the graphical model to represent the structural characteristics of individual 3D model. Finally, we leverage the graph matching algorithm for similarity measure between pairwise 3D models. We evaluate this unified framework on several well-known 3D model datasets. The comparison experiments demonstrate that this unified framework can achieve competing performances against the state of the arts.

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Acknowledgments

This work was supported by National High-Tech Research and Development Program of China (863 programs, 2012AA10A401 and 2012AA092205), Grants of the Major State Basic Research Development Program of China (973 programs, 2012CB114405), National Natural Science Foundation of China (21106095), National Key Technology R&D Program (2011BAD13B07 and 2011BAD13B04), Tianjin Research Program of Application Foundation and Advanced Technology (15JCYBJC30700), Project of introducing one thousand high level talents in three years, Foundation of Introducing Talents to Tianjin Normal University(5RL123), “131” Innovative Talents cultivation of Tianjin, Academic Innovation Foundation of Tianjin Normal University (52XC1403).

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Authors and Affiliations

  1. Tianjin Key Laboratory of Animal and Plant Resistance/College of Life Sciences, Tianjin Normal University, Tianjin, 300387, China

    Tong Hao, Qian Wang, Dan Wu & Jin-Sheng Sun

  2. Tianjin Aquatic Animal Infectious Disease Control and Prevention Center, Tianjin, 300221, China

    Jin-Sheng Sun

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  1. Tong Hao
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  2. Qian Wang
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  4. Jin-Sheng Sun
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Correspondence to Jin-Sheng Sun.

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Hao, T., Wang, Q., Wu, D. et al. A unified framework for cross-modality 3D model retrieval. Multimed Tools Appl 76, 20217–20230 (2017). https://doi.org/10.1007/s11042-017-4417-3

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  • DOI: https://doi.org/10.1007/s11042-017-4417-3

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