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Sketch-based 3D shape retrieval has become an important research topic in content-based 3D object retrieval. The aim of this track is to measure and compare the performance of sketch-based 3D shape retrieval methods based on a large scale hand-drawn sketch query dataset which has 7200 sketches and a generic 3D model target dataset containing 1258 3D models.(More)
Sketch-based 3D model retrieval is very important for applications such as 3D modeling and recognition. In this paper, a sketch-based retrieval algorithm is proposed based on a 3D model feature named View Context and 2D relative shape context matching. To enhance the accuracy of 2D sketch-3D model correspondence as well as the retrieval performance, we(More)
To improve the retrieval performance on a classified 3D model database, we propose a 3D model retrieval algorithm based on a hybrid 3D shape descriptor ZFDR and a class-based retrieval approach CBR utilizing the existing class information of the database. The hybrid 3D shape descriptor ZFDR comprises four features, depicting a 3D model from different(More)
We have created a new benchmarking dataset for testing non-rigid 3D shape retrieval algorithms, one that is much more challenging than existing datasets. Our dataset features exclusively human models, in a variety of body shapes and poses. 3D models of humans are commonly used within computer graphics and vision, and so the ability to distinguish between(More)
This paper proposes a non-photorealistic rendering method that creates an artistic effect called mosaicing. The proposed method converts images provided by the user into the mosaic images. Commercial image editing applications also provide a similar function. However, these applications often trade results for low-cost computing. It is desirable to create(More)
Searching for relevant 3D models based on hand-drawn sketches is both intuitive and important for many applications , such as sketch-based 3D modeling and recognition. We propose a sketch-based 3D model retrieval algorithm by utilizing viewpoint entropy-based adaptive view clustering and shape context matching. Different models have different visual(More)
Large-scale 3D shape retrieval has become an important research direction in content-based 3D shape retrieval. To promote this research area, two Shape Retrieval Contest (SHREC) tracks on large scale comprehensive and sketch-based 3D model retrieval have been organized by us in 2014. Both tracks were based on a unified large-scale benchmark that supports(More)
The objective of this track is to evaluate the performance of 3D shape retrieval approaches on a large-sale comprehensive 3D shape database that contains different types of models, such as generic, articulated, CAD and architecture models. The track is based on a new comprehensive 3D shape benchmark, which contains 8,987 triangle meshes that are classified(More)
Keywords: Sketch-based 3D model retrieval Evaluation SHREC contest Large-scale Benchmark a b s t r a c t Sketch based 3D shape retrieval has become an important research topic in content based 3D object retrieval. To foster this research area, two Shape Retrieval Contest (SHREC) tracks on this topic have been organized by us in 2012 and 2013 based on a(More)