SHREC’14 Track: Shape Retrieval of Non-Rigid 3D Human Models

Abstract

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 body shapes is an important shape retrieval problem. In this track nine groups have submitted the results of a total of 22 different methods which have been tested on our new dataset.

Extracted Key Phrases

3 Figures and Tables

Showing 1-10 of 34 references

Spectral Geometric Methods for Deformable 3D Shape Retrieval. Master's thesis

  • Li C
  • 2013
Showing 1-10 of 20 extracted citations
0102030201520162017
Citations per Year

Citation Velocity: 14

Averaging 14 citations per year over the last 3 years.

Learn more about how we calculate this metric in our FAQ.