Alvey MMI-007 Vehicle Exemplar: Image Segmentation and Attribute Generation

Abstract

The MMI-007 project uses both bottom-up and top-down strategies to deal with the difficult problem of object recognition in outdoor scenes. Within this scheme, bottom-up methods fulfil the requirements of providing a concise image description suitable for symbolic reasoning and of providing an initial set of hypotheses to 'bootstrap' the top-down processes. The nature of the imagery does not lend itself easily to the derivation of precise 3-D structural information by optical-flow or stereo techniques. This leads us to call upon a range of static segmentation techniques, each individually capable of capturing some aspect of the diffuse information present in our images. For example, surface, texture and colour homogenity, and boundary smoothness and continuity.

Alvey MMI-007 Vehicle Exemplar: Evaluation and Verification of Model Instances

“…This paper deals with the "test" part of the strategy. It assumes the image has already been sufficiently processed to produce an hypothesised instance of a known object [See Godden 1987, Morion 1987, Hutbcr 1987. What is then required is a method for quantifying the acceptability of this hypothesis.…”