An approach to knowledge-driven segmentation

Hyde, J.R.; Fullwood, J A; Corrall, D R

doi:10.1016/0262-8856(85)90008-3

Cited by 6 publications

(1 citation statement)

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“…The MMI-007 strategy is a mixed one, combining bottom-up (data driven) analysis, evidential reasoning and precise 3-D model-matching on specific objects of interest. The rationale behind this approach is discussed in Baker and Sullivan (1987) and (from the MCCS point-of-view) in Hyde et al (1985).…”

Section: Introductionmentioning

confidence: 99%

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

Godden¹,

Fullwood²,

Hyde³

1987

Procedings of the Alvey Vision Conference 1987

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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.

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Section: Introductionmentioning

confidence: 99%