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Recently, the development of 3D model database systems and retrieval components are becoming increasingly important due to a rapidly growing amount of available 3D models. This has made the retrieval for specific 3D models become a vital issue. Unfortunately, traditional keyword searching techniques are not always
Automatically assigning keywords to 3D models is of great interest as it allows one to retrieve, index, organize and understand large collections of 3D models. Most Methods require high sample size for training, so the data quality is in high demand. For small scale labeled data set, we propose a semi-supervised
As an important part of multimedia retrieval, researches on 3D model retrieval concentrate on the shape-based retrieval method. It is a promising way to improve retrieval performance by adopting semantic information. At present, semantics of an object is usually represented by several keywords. However, acquiring each
and the hybrid method based on content and semantic. First, the semantic tree is adopted to illustrate models' semantic relationship and the accurate semantic of each tree node is described with several keywords. The semantic tree of all 1814 models of the Princeton Shape Benchmark is constructed. Second, the paper
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