SHREC’19 Track: Extended 2D Scene Image-Based 3D Scene Retrieval

The 3D Shape Retrieval Contest 2010 (SHREC’10) on range scan retrieval aims at comparing algorithms that match a range scan to complete 3D models in a target database1. The queries

Our approach is based on the observation that many geometric feature based shape descriptors—also global ones—can be localized in the fol- lowing sense: first the shape is

Figure 7 and Figure 8 display the Precision-recall curves of the best runs (i.e. Ohbuchi’s MR-BF-DSIFT-E, Smeets’s DMEVD_run1, and Wuhrer’s CF) of each group mea- sured for every

Four families of methods were evaluated in this bench- mark: visual similarity methods [LRS, LGS10] (abbreviated as VS), part-based (PB) bags of words [TCF09], Shape- Google (SG)

6) Hybrid Shape Descriptor ZFDR Distance Computa- tion: The hybrid shape descriptor ZFDR of a model is a combination of Zernike moments feature Z, Fourier descrip- tor F,

2) Feature Distance: A computationally efficient inte- grated image descriptor named ZFEC is adopted for View Context computation. It contains a region-based Zernike moments feature

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

The study revealed an overwhelming support of the 3D autostereoscopic display compared to a 2D display regarding depth judgment, task completion time and the number of required