A New Shape Benchmark for 3D Object Retrieval

A New Shape Benchmark for 3D Object
Retrieval
1 1 1,2 1Rui Fang ,AfzalGodil, Xiaolan Li , and Asim Wagan
1 National Institute of Standards and Technology, Maryland, U.S.A
2 Zhejiang Gongshang University, P. R. China
{rfang,godil,lixlan,wagan}@nist.gov
Abstract. Recently, content based 3D shape retrieval has been an active
area of research. Benchmarking allows researchers to evaluate the quality
of results of different 3D shape retrieval approaches. Here, we propose
a new publicly available 3D shape benchmark to advance the state of
art in 3D shape retrieval. We provide a review of previous and recent
benchmarking efforts and then discuss some of the issues and problems
involved in developing a benchmark. A detailed description of the new
shape benchmark is provided including some of the salient features of
this benchmark. In this benchmark, the 3D models are classified mainly
according to visual shape similarity but in contrast to other benchmarks,
the geometric structure of each model is modified and normalized, with
each class in the benchmark sharing the equal number of models to reduce
the possible bias in evaluation results. In the end we evaluate several
representative algorithms for 3D shape searching on the new benchmark,
and a comparison experiment between different shape benchmarks is also
conducted to show the reliability of the new benchmark.
1 Introduction
With the increasing number of 3D models created and available on the Inter-
net, many domains have their own ...