Titlebook: Object Representation in Computer Vision II; ECCV ‘96 Internation Jean Ponce,Andrew Zisserman,Martial Hebert Conference proceedings 1996 Sp

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書目名稱Object Representation in Computer Vision II影響因子(影響力)




書目名稱Object Representation in Computer Vision II影響因子(影響力)學科排名




書目名稱Object Representation in Computer Vision II網(wǎng)絡公開度




書目名稱Object Representation in Computer Vision II網(wǎng)絡公開度學科排名




書目名稱Object Representation in Computer Vision II被引頻次




書目名稱Object Representation in Computer Vision II被引頻次學科排名




書目名稱Object Representation in Computer Vision II年度引用




書目名稱Object Representation in Computer Vision II年度引用學科排名




書目名稱Object Representation in Computer Vision II讀者反饋




書目名稱Object Representation in Computer Vision II讀者反饋學科排名

medieval

0302-9743 omputer Vision., held in conjunction with ECCV ‘96 in Cambridge, UK, in April 1996..The 15 revised full papers contained in the book were selected from 45 submissions for presentation at the workshop. Also included are three invited contributions based on the talks by Takeo Kanade, Jan Koenderink, a

OREX

nerve-sparing

絆住

Representing objects using topology,logy relates to that of the scene, we demonstrate how it can be extracted from raw images. Subsequent to this, we describe how the newly found topological descriptions can be employed to facilitate feature grouping, the recognition of polyhedra, and the evaluation of recognition hypothesis which result from a mature object recognition system.

clarify

Curvature based signatures for object description and recognition,ted that is rotation, translation, and, scale invariant. This signature is shown to be invariant over large ranges of poses of the same objects, while being significantly different between distinctly shaped objects. A new object recognition methodology is proposed by compiling signatures for only a few poses of a given object.

Assault

Learning object representations from lighting variations,t when the integrability constraint is applied to objects with varying albedo it leads to an ambiguity in depth estimation similar to the bas relief ambiguity. The integrability constraint, however, is useful for resolving ambiguities which arise in current photometric theories.

一罵死割除

Learning appearance models for object recognition,y the model to guide the search for a match between model and image. Experiments show the method capable of learning to recognize complex objects in cluttered images, acquiring models that represent those objects using relatively few views.

排出

Missile

On 3D shape synthesis,wo known curvature distributions,and then mapping the interpolated curvature distribution back to a 3D morph. Using the distance between two curvature distributions, we can quantitatively control the shape synthesis process to yield smooth curvature migration. Experiments show that our method produces smooth and realistic shape morphs.