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Computational Symmetry in Computer Vision and Computer Graphics
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TLDR
Recognizing the fundamental relevance and group theory of symmetry has the potential to play an important role in computational sciences.Abstract:
In the arts and sciences, as well as in our daily lives, symmetry has made a profound and lasting impact. Likewise, a computational treatment of symmetry and group theory (the ultimate mathematical formalization of symmetry) has the potential to play an important role in computational sciences. Though the term Computational Symmetry was formally defined a decade ago by the first author, referring to algorithmic treatment of symmetries, seeking symmetry from digital data has been attempted for over four decades. Computational symmetry on real world data turns out to be challenging enough that, after decades of effort, a fully automated symmetry-savvy system remains elusive for real world applications. The recent resurging interests in computational symmetry for computer vision and computer graphics applications have shown promising results. Recognizing the fundamental relevance and potential power that computational symmetry affords, we offer this survey to the computer vision and computer graphics communities. This survey provides a succinct summary of the relevant mathematical theory, a historic perspective of some important symmetry-related ideas, a partial yet timely report on the state of the arts symmetry detection algorithms along with its first quantitative benchmark, a diverse set of real world applications, suggestions for future directions and a comprehensive reference list.read more
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TL;DR: In this paper, the authors offer a new book that enPDFd the perception of the visual world to read, which they call "Let's Read". But they do not discuss how to read it.
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Image completion using planar structure guidance
TL;DR: This work proposes a method for automatically guiding patch-based image completion using mid-level structural cues by first estimates planar projection parameters, softly segments the known region into planes, and discovers translational regularity within these planes.
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TILT: Transform Invariant Low-Rank Textures
TL;DR: This method can accurately recover both the intrinsic low-rank texture and the unknown transformation, and hence both the geometry and appearance of the associated planar region in 3D in the case of planar regions with significant affine or projective deformation.
References
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Eigenfaces for recognition
Matthew Turk,Alex Pentland +1 more
TL;DR: A near-real-time computer system that can locate and track a subject's head, and then recognize the person by comparing characteristics of the face to those of known individuals, and that is easy to implement using a neural network architecture.
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Eigenfaces vs. Fisherfaces: recognition using class specific linear projection
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Microstructure of a spatial map in the entorhinal cortex
TL;DR: The dorsocaudal medial entorhinal cortex (dMEC) contains a directionally oriented, topographically organized neural map of the spatial environment, whose key unit is the ‘grid cell’, which is activated whenever the animal's position coincides with any vertex of a regular grid of equilateral triangles spanning the surface of the environment.
Proceedings ArticleDOI
Robust wide baseline stereo from maximally stable extremal regions
TL;DR: The wide-baseline stereo problem, i.e. the problem of establishing correspondences between a pair of images taken from different viewpoints, is studied and an efficient and practically fast detection algorithm is presented for an affinely-invariant stable subset of extremal regions, the maximally stable extremal region (MSER).