3D object modeling and recognition using affine-invariant patches and multi-view spatial constraints
Published 22 December 2003Open access
Fred Rothganger, Svetlana Lazebnik, C. Schmid, Jean Ponce
Citations127
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
Multi-view constraints associated with groups of patches are combined with a normalized representation of their appearance to guide matching and reconstruction, allowing the acquisition of true three-dimensional affine and Euclidean models from multiple images and their recognition in a single photograph taken from an arbitrary viewpoint.
Abstract
International audience
Keywords
Computer ScienceEngineering
Cambridge University Press eBooksMultiple View Geometry in Computer Vision
20,788 Citations2004Richard Hartley, Andrew Zisserman
Object recognition from local scale-invariant features
16,195 Citations1999David Lowe
Experimental results show that robust object recognition can be achieved in cluttered partially occluded images with a computation time of under 2 seconds.
A Combined Corner and Edge Detector
12,478 Citations1988Chris Harris, Matthew J. Stephens
The problem the authors are addressing in Alvey Project MMI149 is that of using computer vision to understand the unconstrained 3D world, in which the viewed scenes will in general contain too wide a diversity of objects for topdown recognition techniques to work.
International Journal of Computer VisionShape and motion from image streams under orthography: a factorization method
2,884 Citations1992Carlo Tomasi, Takeo Kanade
A factorization method is developed that can overcome the difficulty by recovering shape and motion under orthography without computing depth as an intermediate step, and gives accurate results.
International Journal of Computer VisionVisual learning and recognition of 3-d objects from appearance
1,891 Citations1995Hiroshi Murase, Shree K. Nayar
A near real-time recognition system with 20 complex objects in the database has been developed and a compact representation of object appearance is proposed that is parametrized by pose and illumination.
IEEE Transactions on Pattern Analysis and Machine IntelligenceLocal grayvalue invariants for image retrieval
1,426 Citations1997C. Schmid, Roger Mohr
This paper addresses the problem of retrieving images from large image databases with a method based on local grayvalue invariants which are computed at automatically detected interest points and allows for efficient retrieval from a database of more than 1,000 images.
Lecture notes in computer scienceAn Affine Invariant Interest Point Detector
1,300 Citations2002Krystian Mikolajczyk, Cordelia Schmid
A novel approach for detecting affine invariant interest points that can deal with significant affine transformations including large scale changes and shows an excellent performance in the presence of large perspective transformations including significant scale changes.
Indexing based on scale invariant interest points
1,090 Citations2002Krystian Mikolajczyk, C. Schmid
The method is based on two recent results on scale space: interest points can be adapted to scale and give repeatable results (geometrically stable) and local extrema over scale of normalized derivatives indicate the presence of characteristic local structures.
A statistical method for 3D object detection applied to faces and cars
1,061 Citations2002Henry Schneiderman, Takeo Kanade
Using this method, this work has developed the first algorithm that can reliably detect human faces with out-of-plane rotation and the first algorithms thatCan reliably detect passenger cars over a wide range of viewpoints.
MIT Press eBooksGeometric invariance in computer vision
1,022 Citations1992Joseph L. Mundy, Andrew Zisserman
Part 1 foundations: algebraic invariants - invariant theory and enumerative combinatorics of young tableaux, and applications: transformation invariant indexing and invariant linear methods in photogrammetry and model-matching.
Reliable feature matching across widely separated views
624 Citations2002Adam Baumberg
A robust method for automatically matching features in images corresponding to the same physical point on an object seen from two arbitrary viewpoints that is optimised for a structure-from-motion application where it wishes to ignore unreliable matches at the expense of reducing the number of feature matches.
The MIT Press eBooksThe Geometry of Multiple Images
601 Citations2001Olivier Faugeras, Quang-Tuan Luong +1 more
Lecture notes in computer scienceUnsupervised Learning of Models for Recognition
599 Citations2000Markus Weber, Max Welling +1 more
A method to learn object class models from unlabeled and unsegmented cluttered cluttered scenes for the purpose of visual object recognition that achieves very good classification results on human faces and rear views of cars.
Lecture notes in computer scienceMulti-view Matching for Unordered Image Sets, or “How Do I Organize My Holiday Snaps?”
525 Citations2002F. Schaffalitzky, Andrew Zisserman
This paper invests how a combination of image invariants, covariants, and multiple view relations can be used in concord to enable efficient multiple view matching and produces a matching algorithm which is linear in the number of views.
Local feature view clustering for 3D object recognition
481 Citations2005David Lowe
This paper presents a method for combining multiple images of a 3D object into a single model representation that provides for recognition of 3D objects from any viewpoint, the generalization of models to non-rigid changes, and improved robustness through the combination of features acquired under a range of imaging conditions.
Wide baseline stereo matching
275 Citations2002P. Pritchett, Andrew Zisserman
The objective of this work is to enlarge the class of camera motions for which epipolar geometry and image correspondences can be computed automatically, and to facilitate matching between quite disparate views-wide baseline stereo.
Image and Vision ComputingSurface matching for object recognition in complex three-dimensional scenes
235 Citations1998Andrew Johnson, Martial Hebert
The effectiveness of the object representation comes from its ability to combine the descriptive nature of global object properties with the robustness to partial views and clutter of local shape descriptions and the wide applicability of the algorithm is demonstrated with results showing recognition of complex objects in cluttered scenes with occlusion.
International Journal of Computer VisionThe viewpoint consistency constraint
209 Citations1987David Lowe
It will be shown that the effective application of the viewpoint consistency constraint, in conjunction with bottom-up image description based upon principles of perceptual organization, can lead to robust three-dimensional object recognition from single gray-scale images.
IEEE Transactions on Pattern Analysis and Machine IntelligenceView variation of point-set and line-segment features
156 Citations1993J. Brian Burns, Richard Weiss +1 more
The variation, with respect to view, of 2D features defined for projections of 3D point sets and line segments is studied and it is established that general-case view-invariants do not exist for any number of points, given true perspective, weak perspective, or orthographic projection models.
Lecture notes in computer scienceWide Baseline Point Matching Using Affine Invariants Computed from Intensity Profiles
94 Citations2000Dennis Tell, Stefan Carlsson
An algorithm which is capable of handling larger changes in viewpoint than classical correlation based techniques is proposed, which works by computing affinely invariant fourier features from intensity profiles in each image.
International Journal of Computer VisionProbabilistic Models of Appearance for 3-D Object Recognition
91 Citations2000Arthur R. Pope, David Lowe
This work describes how to model the appearance of a 3-D object using multiple views, learn such a model from training images, and use the model for object recognition, and demonstrates that OLIVER is capable of learning to recognize complex objects in cluttered images, while acquiring models that represent those objects using relatively few views.
