@article{zou2014viewpoint-aware,
author = {Zou, Changqing and Wang, Changhu and Wen, Yafei and Zhang, Lei and Liu, Jiangzhuang},
title = {Viewpoint-Aware Representation for Sketch-Based 3D Model Retrieval},
year = {2014},
month = {July},
abstract = {We study the problem of sketch-based 3D model retrieval,
and propose a solution powered by a new query-to-model
distance metric and a powerful feature descriptor based on
the bag-of-features framework. The main idea of the proposed
query-to-model distance metric is to represent a query sketch
using a compact set of sample views (called basic views) of
each model, and to rank the models in ascending order of the
representation errors. To better differentiate between relevant
and irrelevant models, the representation is constrained to be
essentially a combination of basic views with similar viewpoints.
In another aspect, we propose a mid-level descriptor (called
BOF-JESC) which robustly characterizes the edge information
within junction-centered patches, to extract the salient shape
features from sketches or model views. The combination of the
query-to-model distance metric and the BOF-JESC descriptor
achieves effective results on two latest benchmark datasets},
url = {http://approjects.co.za/?big=en-us/research/publication/viewpoint-aware-representation-sketch-based-3d-model-retrieval/},
journal = {IEEE Signal Processing Letters},
}