State of the Art in Shape Matching

By Remco C. Veltkamp, M. Hagedoorn. Principles of Visual Information Retrieval, 2001

661 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/3903efd2e310224ae987c0d43809650e0177d0bc

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In Computer Vision and Pattern Recognition

Citations in the corpus

Matching with shape contexts (2000, background): “For a more detailed discussion of the variety of shape matching techniques, the reader is referred to [28].”
Matching 3D models with shape distributions (2001, methodology): “For a broad introduction to shape matching methods, please refer to any of several survey papers [2, 7, 14, 41, 44, 57].”
Matching shapes (2001, background): “In his classic work On Growth and Form [27], Thompson observed that related but not identical shapes can often be deformed into alignment using simple coordinate transformations.”
Shape Matching and Object Recognition Using Shape Contexts (2002, background): “An extensive survey of shape matching in computer vision can be found in [58, 22].”
A Reflective Symmetry Descriptor (2002, methodology): “In this respect, our goals are similar to previously described shape descriptors [17,18,19,20], of which some recent examples include spin images [21], harmonic shape images [22], shape contexts[23,24], and Extended Gaussian Images [25].”
Shape Classification Using the Inner-Distance (2007, background): “For general shape matching, a recent review is given in [45].”
Shape distributions (2002, methodology): “Other methods, perhaps based on 2D curve matching [2, 70], could also be used.”
Shape Context: A New Descriptor for Shape Matching and Object Recognition (2000, neutral): “(For a recent overview, see [16].)”
A review of content-based image retrieval systems in medical applications - clinical benefits and future directions (2004, methodology): “[50] R.”
Learning compact 3D models of indoor and outdoor environments with a mobile robot (2003, background): “Furthermore, there are several approaches that consider the problem of shape matching [20].”
Skeleton based shape matching and retrieval (2003, background): “While any skeletonization process is generally sensitive to noise on the boundary (slight movements of voxels, or the addition of bumps and breaks) [37, 29], the overall impact of noise is reduced because of the clustering and thinness parameter.”
Shape Priors for Level Set Representations (2002, background): “A complete review of the literature in shape matching can be found in [23].”
Three-dimensional shape searching: state-of-the-art review and future trends (2005, neutral): “[23,34–39].”