Three-dimensional computer vision: a geometric viewpoint
Three-dimensional computer vision: a geometric viewpoint
Wavelet-Based Affine Invariant Representation: A Tool for Recognizing Planar Objects in 3D Space
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Geometry of Algorithms with Orthogonality Constraints
SIAM Journal on Matrix Analysis and Applications
Recognition, Resolution, and Complexity of Objects Subject to Affine Transformations
International Journal of Computer Vision
Reliable and Efficient Pattern Matching Using an Affine Invariant Metric
International Journal of Computer Vision
Autocalibration from Planar Scenes
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Recursive Structure and Motion from Image Sequences using Shape and Depth Spaces
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
ICPR '96 Proceedings of the 1996 International Conference on Pattern Recognition (ICPR '96) Volume I - Volume 7270
A new point matching algorithm for non-rigid registration
Computer Vision and Image Understanding - Special issue on nonrigid image registration
Intrinsic Statistics on Riemannian Manifolds: Basic Tools for Geometric Measurements
Journal of Mathematical Imaging and Vision
Computationally efficient wavelet affine invariant functions for shape recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image registration and object recognition using affine invariants and convex hulls
IEEE Transactions on Image Processing
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We define the space of affine shapes of k points in R n to be the topological quotient of (R n ) k modulo the natural action of the affine group of R n . These spaces arise naturally in many image-processing applications, and despite having poor separation properties, have some topological and geometric properties reminiscent of the more familiar Procrustes shape spaces Σ n k in which one identifies configurations related by an orientation-preserving Euclidean similarity transformation. We examine the topology of the connected, non-Hausdorff spaces Sh n k in detail. Each Sh n k is a disjoint union of naturally ordered strata, each of which is homeomorphic in the relative topology to a Grassmannian, and we show how the strata are attached to each other. The top stratum carries a natural Riemannian metric, which we compute explicitly for kn, expressing the metric purely in terms of "pre-shape" data, i.e. configurations of k points in R n .