Linked Life Data

1359588

Source:http://linkedlifedata.com/resource/pubmed/id/1359588

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1281
pubmed:dateCreated
1992-12-23
pubmed:abstractText
This paper discusses two problems related to three-dimensional object recognition. The first is segmentation and the selection of a candidate object in the image, the second is the recognition of a three-dimensional object from different viewing positions. Regarding segmentation, it is shown how globally salient structures can be extracted from a contour image based on geometrical attributes, including smoothness and contour length. This computation is performed by a parallel network of locally connected neuron-like elements. With respect to the effect of viewing, it is shown how the problem can be overcome by using the linear combinations of a small number of two-dimensional object views. In both problems the emphasis is on methods that are relatively low level in nature. Segmentation is performed using a bottom-up process, driven by the geometry of image contours. Recognition is performed without using explicit three-dimensional models, but by the direct manipulation of two-dimensional images.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Sep
pubmed:issn
0962-8436
pubmed:author
pubmed:issnType
Print
pubmed:day
29
pubmed:volume
337
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
371-8; discussion 379
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
1992
pubmed:articleTitle
Low-level aspects of segmentation and recognition.
pubmed:affiliation
Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge 02139.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, Non-P.H.S.