3D model retrieval using Bag-of-View-Words
The view-based 3D model descriptors, which represent a 3D model using its projected views, have limitations on viewpoints sampling and computational cost. This paper proposes a new 3D model descriptor, called the Bag-of-View-Words(BoVW) descriptor, which describes a 3D model by measuring the occurrences of its projected views. An adaptive clustering method is applied to reduce the redundancy of the projected views of each 3D model. A 3D model is represented by a multi-resolution histogram, which is combined by several BoVW descriptors at different levels. The codebook is obtained by unsupervised learning. We also propose a new pyramid matching method for 3D model comparison. Experimental results demonstrated that our method outperforms several existing 3D model descriptors in respect of retrieval precision and computational cost.
3d model retrieval 3d model descriptor pyramid matching bag-of-view words