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Sketch-Based 3D Model Retrieval Using Attributes

Sketch-Based 3D Model Retrieval Using Attributes

Haopeng Lei, Guoliang Luo, Yuhua Li, Jianming Liu, Jihua Ye
Copyright: © 2018 |Volume: 10 |Issue: 3 |Pages: 16
ISSN: 1938-0259|EISSN: 1938-0267|EISBN13: 9781522543381|DOI: 10.4018/IJGHPC.2018070105
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MLA

Lei, Haopeng, et al. "Sketch-Based 3D Model Retrieval Using Attributes." IJGHPC vol.10, no.3 2018: pp.60-75. https://doi.org/10.4018/IJGHPC.2018070105

APA

Lei, H., Luo, G., Li, Y., Liu, J., & Ye, J. (2018). Sketch-Based 3D Model Retrieval Using Attributes. International Journal of Grid and High Performance Computing (IJGHPC), 10(3), 60-75. https://doi.org/10.4018/IJGHPC.2018070105

Chicago

Lei, Haopeng, et al. "Sketch-Based 3D Model Retrieval Using Attributes," International Journal of Grid and High Performance Computing (IJGHPC) 10, no.3: 60-75. https://doi.org/10.4018/IJGHPC.2018070105

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Abstract

With the rapid growth of available 3D models on the Internet, how to retrieve 3D models based on hand-drawn sketch retrieval are becoming increasingly important. This article proposes a new sketch-based 3D model retrieval approach. This approach is different from current methods that make use of low-level visual features to capture the search intention of users. The proposed method uses two kinds of semantic attributes, including pre-defined attributes and latent attributes. Specifically, pre-defined attributes are defined manually which can provide prior knowledge about different sketch categories and latent-attributes are more discriminative which can differentiate sketch categories at a finer level. Therefore, these semantic attributes can provide a more descriptive and discriminative meaningful representation than low-level feature descriptors. The experiment results demonstrate that this proposed method can achieve superior performance over previously proposed sketch-based 3D model retrieval methods.

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