Sketch-Based 3D Model Retrieval Using Attributes
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.
Year of publication: |
2018
|
---|---|
Authors: | Lei, Haopeng ; Luo, Guoliang ; Li, Yuhua ; Liu, Jianming ; Ye, Jihua |
Published in: |
International Journal of Grid and High Performance Computing (IJGHPC). - IGI Global, ISSN 1938-0267, ZDB-ID 2703335-1. - Vol. 10.2018, 3 (01.07.), p. 60-75
|
Publisher: |
IGI Global |
Subject: | 3D Model Retrieval | Low-Level Feature | Semantic Attributes | Visual Words |
Saved in:
Online Resource
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