Huttenlocher, Daniel Peter
Overview
Works:  2 works in 5 publications in 1 language and 9 library holdings 

Roles:  Author 
Classifications:  Q335.M41, 
Publication Timeline
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Most widely held works by
Daniel Peter Huttenlocher
Threedimensional recognition of solid objects from a twodimensional image by D Huttenlocher(
Book
)
3 editions published in 1988 in English and held by 7 WorldCat member libraries worldwide
This thesis addresses the problem of recognizing solid objects in the threedimensional world, using twodimensional shape information extracted from a single image. Objects can be partly occluded and can occur in cluttered scenes. A model based approach is taken, where stored models are matched to an image. The matching problem is separated into two stages, which employ different representations of objects. The first stage uses the smallest possible number of local features to find transformations from a model to an image. This minimizes the amount of search required in recognition. The second stage uses the entire edge contour of an object to verify each transformation. This reduces the chance of finding false matches. A new method is developed for computing transformations from a model to an image. It is shown that when perspective viewing is approximated by orthographic projection plus scale, three corresponding model and image points define a unique transformation, up to a reflection. The solution method based on this result only involves second order equations, and thus is fast and robust. Recognizing objects under projection requires features that are relatively stable over changes in viewpoint. Stable features are obtained by segmenting edge contours at zeroes of curvature, because these points are preserved under projection. Each feature defines either a point and an orientation or three points, so only one or two features are needed to compute a transformation. Thus the number of transformations considered in recognition is only quadratic in the number of corresponding model and image features. (kr)
3 editions published in 1988 in English and held by 7 WorldCat member libraries worldwide
This thesis addresses the problem of recognizing solid objects in the threedimensional world, using twodimensional shape information extracted from a single image. Objects can be partly occluded and can occur in cluttered scenes. A model based approach is taken, where stored models are matched to an image. The matching problem is separated into two stages, which employ different representations of objects. The first stage uses the smallest possible number of local features to find transformations from a model to an image. This minimizes the amount of search required in recognition. The second stage uses the entire edge contour of an object to verify each transformation. This reduces the chance of finding false matches. A new method is developed for computing transformations from a model to an image. It is shown that when perspective viewing is approximated by orthographic projection plus scale, three corresponding model and image points define a unique transformation, up to a reflection. The solution method based on this result only involves second order equations, and thus is fast and robust. Recognizing objects under projection requires features that are relatively stable over changes in viewpoint. Stable features are obtained by segmenting edge contours at zeroes of curvature, because these points are preserved under projection. Each feature defines either a point and an orientation or three points, so only one or two features are needed to compute a transformation. Thus the number of transformations considered in recognition is only quadratic in the number of corresponding model and image features. (kr)
Acousticphonetic and lexical constraints in word recognition: lexical access using partial information by Daniel Peter Huttenlocher(
Book
)
2 editions published in 1984 in English and held by 2 WorldCat member libraries worldwide
2 editions published in 1984 in English and held by 2 WorldCat member libraries worldwide
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