** See download links below**

Much of our discovery science work on high-level vision is based on computer generated novel object sets that we have developed over several years. The object sets were developed to allow for control of object geometry, similarity and familiarity. The stimuli (including the mesh models, and rendered versions) are now directly (and freely!) available for other labs to use. The mesh models can be rendered as stereo images (e.g., either for VR systems, interlaced or anaglyphic presentation) in most commercially available modelling packages (e.g., Strata3D) or Matlab etc. We also have stereo rendered versions of the objects available upon request. 

The base object set comprises 48 mesh models of complex, multi-part, novel objects in .obj format (see download links below). The set is constructed to comprise 12 base 'target' objects each with three distracters that share either local volumetric parts but not global 3D configuration (SD); share global 3D configuration but not local parts (DS) or share neither local parts or global 3D configuration (DD). 

We also have pre-rendered sets of the models available 48 objects x 6 viewpoints (288 image files). 

Some examples of how we have used the object set/s in a recent ERP and eye tracking studies can be found in (please use these papers as citations if you intend to use our stimuli in your work):

Oliver, Z. J., Cristino, F., Roberts, M. V., Pegna, A. J., & Leek, E. C. (2017). Stereo viewing modulates three-dimensional shape processing during object recognition: A high-density ERP study. Journal of experimental psychology. Human perception and performance, 44(4), 518–534. doi:10.1037/xhp0000444 

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5896504/ 

E. Charles Leek, Filipe Cristino, Lina I. Conlan, Candy Patterson, Elly Rodriguez, Stephen J. Johnston; Eye movement patterns during the recognition of three-dimensional objects: Preferential fixation of concave surface curvature minima. Journal of Vision2012;12(1):7. doi: 10.1167/12.1.7. 

https://jov.arvojournals.org/article.aspx?articleid=2192169 

Download the mesh models below (any problems please email: charles.leek@liverpool.ac.uk):