Anytime perceptual grouping of 2D features into 3D basic shapes

Abstract

2D perceptual grouping is a well studied area which still has its merits even in the age of powerful object recognizer, namely when no prior object knowledge is available. Often perceptual grouping mechanisms struggle with the runtime complexity stemming from the combinatorial explosion when creating larger assemblies of features, and simple thresholding for pruning hypotheses leads to cumbersome tuning of parameters. In this work we propose an incremental approach instead, which leads to an anytime method, where the system produces more results with longer runtime. Moreover the proposed approach lends itself easily to incorporation of attentional mechanisms. We show how basic 3D object shapes can thus be detected using a table plane assumption. © 2013 Springer-Verlag.