A method of recognising a simple object in a cluttered scene is described, which uses geometrical models to express detailed knowledge about the object and the scene. Salient features of the object serve as cues which guide a search for an appropriate instance of the model; a pre-processor identifies a minimal set of tests for the cue. The method is demonstrated by a program which detects London buses in street scenes, but may be applied to a wide variety of other visual tasks.
G D Sullivan,
K D Baker,
"Model-Based Vision: Using Cues To Select Hypotheses", Proc. SPIE 0654, Automatic Optical Inspection, (17 November 1986); doi: 10.1117/12.938300; https://doi.org/10.1117/12.938300