@inproceedings{3133,
abstract = {This note contributes to the point calculus of persistent homology by extending Alexander duality from spaces to real-valued functions. Given a perfect Morse function f: S n+1 →[0, 1 and a decomposition S n+1 = U ∪ V into two (n + 1)-manifolds with common boundary M, we prove elementary relationships between the persistence diagrams of f restricted to U, to V, and to M. },
author = {Edelsbrunner, Herbert and Kerber, Michael},
booktitle = {Proceedings of the twenty-eighth annual symposium on Computational geometry },
location = {Chapel Hill, NC, USA},
pages = {249 -- 258},
publisher = {ACM},
title = {{Alexander duality for functions: The persistent behavior of land and water and shore}},
doi = {10.1145/2261250.2261287},
year = {2012},
}
@inproceedings{3134,
abstract = {It has been an open question whether the sum of finitely many isotropic Gaussian kernels in n ≥ 2 dimensions can have more modes than kernels, until in 2003 Carreira-Perpiñán and Williams exhibited n +1 isotropic Gaussian kernels in ℝ n with n + 2 modes. We give a detailed analysis of this example, showing that it has exponentially many critical points and that the resilience of the extra mode grows like √n. In addition, we exhibit finite configurations of isotropic Gaussian kernels with superlinearly many modes. },
author = {Edelsbrunner, Herbert and Fasy, Brittany and Rote, Günter},
booktitle = {Proceedings of the twenty-eighth annual symposium on Computational geometry },
location = {Chapel Hill, NC, USA},
pages = {91 -- 100},
publisher = {ACM},
title = {{Add isotropic Gaussian kernels at own risk: More and more resilient modes in higher dimensions}},
doi = {10.1145/2261250.2261265},
year = {2012},
}
@article{3159,
abstract = {The structure of hierarchical networks in biological and physical systems has long been characterized using the Horton-Strahler ordering scheme. The scheme assigns an integer order to each edge in the network based on the topology of branching such that the order increases from distal parts of the network (e.g., mountain streams or capillaries) to the "root" of the network (e.g., the river outlet or the aorta). However, Horton-Strahler ordering cannot be applied to networks with loops because they they create a contradiction in the edge ordering in terms of which edge precedes another in the hierarchy. Here, we present a generalization of the Horton-Strahler order to weighted planar reticular networks, where weights are assumed to correlate with the importance of network edges, e.g., weights estimated from edge widths may correlate to flow capacity. Our method assigns hierarchical levels not only to edges of the network, but also to its loops, and classifies the edges into reticular edges, which are responsible for loop formation, and tree edges. In addition, we perform a detailed and rigorous theoretical analysis of the sensitivity of the hierarchical levels to weight perturbations. In doing so, we show that the ordering of the reticular edges is more robust to noise in weight estimation than is the ordering of the tree edges. We discuss applications of this generalized Horton-Strahler ordering to the study of leaf venation and other biological networks.},
author = {Mileyko, Yuriy and Edelsbrunner, Herbert and Price, Charles and Weitz, Joshua},
journal = {PLoS One},
number = {6},
publisher = {Public Library of Science},
title = {{Hierarchical ordering of reticular networks}},
doi = {10.1371/journal.pone.0036715},
volume = {7},
year = {2012},
}
@article{3256,
abstract = {We use a distortion to define the dual complex of a cubical subdivision of ℝ n as an n-dimensional subcomplex of the nerve of the set of n-cubes. Motivated by the topological analysis of high-dimensional digital image data, we consider such subdivisions defined by generalizations of quad- and oct-trees to n dimensions. Assuming the subdivision is balanced, we show that mapping each vertex to the center of the corresponding n-cube gives a geometric realization of the dual complex in ℝ n.},
author = {Edelsbrunner, Herbert and Kerber, Michael},
journal = {Discrete & Computational Geometry},
number = {2},
pages = {393 -- 414},
publisher = {Springer},
title = {{Dual complexes of cubical subdivisions of ℝn}},
doi = {10.1007/s00454-011-9382-4},
volume = {47},
year = {2012},
}
@inproceedings{3265,
abstract = {We propose a mid-level statistical model for image segmentation that composes multiple figure-ground hypotheses (FG) obtained by applying constraints at different locations and scales, into larger interpretations (tilings) of the entire image. Inference is cast as optimization over sets of maximal cliques sampled from a graph connecting all non-overlapping figure-ground segment hypotheses. Potential functions over cliques combine unary, Gestalt-based figure qualities, and pairwise compatibilities among spatially neighboring segments, constrained by T-junctions and the boundary interface statistics of real scenes. Learning the model parameters is based on maximum likelihood, alternating between sampling image tilings and optimizing their potential function parameters. State of the art results are reported on the Berkeley and Stanford segmentation datasets, as well as VOC2009, where a 28% improvement was achieved.},
author = {Ion, Adrian and Carreira, Joao and Sminchisescu, Cristian},
location = {Barcelona, Spain},
publisher = {IEEE},
title = {{Image segmentation by figure-ground composition into maximal cliques}},
doi = {10.1109/ICCV.2011.6126486},
year = {2012},
}
@article{3310,
abstract = {The theory of persistent homology opens up the possibility to reason about topological features of a space or a function quantitatively and in combinatorial terms. We refer to this new angle at a classical subject within algebraic topology as a point calculus, which we present for the family of interlevel sets of a real-valued function. Our account of the subject is expository, devoid of proofs, and written for non-experts in algebraic topology.},
author = {Bendich, Paul and Cabello, Sergio and Edelsbrunner, Herbert},
journal = {Pattern Recognition Letters},
number = {11},
pages = {1436 -- 1444},
publisher = {Elsevier},
title = {{A point calculus for interlevel set homology}},
doi = {10.1016/j.patrec.2011.10.007},
volume = {33},
year = {2012},
}
@article{3331,
abstract = {Computing the topology of an algebraic plane curve C means computing a combinatorial graph that is isotopic to C and thus represents its topology in R2. We prove that, for a polynomial of degree n with integer coefficients bounded by 2ρ, the topology of the induced curve can be computed with bit operations ( indicates that we omit logarithmic factors). Our analysis improves the previous best known complexity bounds by a factor of n2. The improvement is based on new techniques to compute and refine isolating intervals for the real roots of polynomials, and on the consequent amortized analysis of the critical fibers of the algebraic curve.},
author = {Kerber, Michael and Sagraloff, Michael},
journal = { Journal of Symbolic Computation},
number = {3},
pages = {239 -- 258},
publisher = {Elsevier},
title = {{A worst case bound for topology computation of algebraic curves}},
doi = {10.1016/j.jsc.2011.11.001},
volume = {47},
year = {2012},
}
@article{3781,
abstract = {We bound the difference in length of two curves in terms of their total curvatures and the Fréchet distance. The bound is independent of the dimension of the ambient Euclidean space, it improves upon a bound by Cohen-Steiner and Edelsbrunner, and it generalizes a result by Fáry and Chakerian.},
author = {Fasy, Brittany Terese},
journal = {Acta Sci. Math. (Szeged)},
number = {1-2},
pages = {359 -- 367},
publisher = {Szegedi Tudományegyetem},
title = {{The difference in length of curves in R^n}},
volume = {77},
year = {2011},
}
@inbook{3796,
abstract = {We address the problem of covering ℝ n with congruent balls, while minimizing the number of balls that contain an average point. Considering the 1-parameter family of lattices defined by stretching or compressing the integer grid in diagonal direction, we give a closed formula for the covering density that depends on the distortion parameter. We observe that our family contains the thinnest lattice coverings in dimensions 2 to 5. We also consider the problem of packing congruent balls in ℝ n , for which we give a closed formula for the packing density as well. Again we observe that our family contains optimal configurations, this time densest packings in dimensions 2 and 3.},
author = {Edelsbrunner, Herbert and Kerber, Michael},
booktitle = {Rainbow of Computer Science},
editor = {Calude, Cristian and Rozenberg, Grzegorz and Salomaa, Arto},
pages = {20 -- 35},
publisher = {Springer},
title = {{Covering and packing with spheres by diagonal distortion in R^n}},
doi = {10.1007/978-3-642-19391-0_2},
volume = {6570},
year = {2011},
}
@article{3965,
abstract = {The elevation function on a smoothly embedded 2-manifold in R-3 reflects the multiscale topography of cavities and protrusions as local maxima. The function has been useful in identifying coarse docking configurations for protein pairs. Transporting the concept from the smooth to the piecewise linear category, this paper describes an algorithm for finding all local maxima. While its worst-case running time is the same as of the algorithm used in prior work, its performance in practice is orders of magnitudes superior. We cast light on this improvement by relating the running time to the total absolute Gaussian curvature of the 2-manifold.},
author = {Wang, Bei and Edelsbrunner, Herbert and Morozov, Dmitriy},
journal = {Journal of Experimental Algorithmics},
number = {2.2},
pages = {1 -- 13},
publisher = {ACM},
title = {{Computing elevation maxima by searching the Gauss sphere}},
doi = {10.1145/1963190.1970375},
volume = {16},
year = {2011},
}
@inproceedings{3266,
abstract = {We present a joint image segmentation and labeling model (JSL) which, given a bag of figure-ground segment hypotheses extracted at multiple image locations and scales, constructs a joint probability distribution over both the compatible image interpretations (tilings or image segmentations) composed from those segments, and over their labeling into categories. The process of drawing samples from the joint distribution can be interpreted as first sampling tilings, modeled as maximal cliques, from a graph connecting spatially non-overlapping segments in the bag [1], followed by sampling labels for those segments, conditioned on the choice of a particular tiling. We learn the segmentation and labeling parameters jointly, based on Maximum Likelihood with a novel Incremental Saddle Point estimation procedure. The partition function over tilings and labelings is increasingly more accurately approximated by including incorrect configurations that a not-yet-competent model rates probable during learning. We show that the proposed methodologymatches the current state of the art in the Stanford dataset [2], as well as in VOC2010, where 41.7% accuracy on the test set is achieved.},
author = {Ion, Adrian and Carreira, Joao and Sminchisescu, Cristian},
booktitle = {NIPS Proceedings},
location = {Granada, Spain},
pages = {1827 -- 1835},
publisher = {Neural Information Processing Systems Foundation},
title = {{Probabilistic joint image segmentation and labeling}},
volume = {24},
year = {2011},
}
@article{3267,
abstract = {We address the problem of localizing homology classes, namely, finding the cycle representing a given class with the most concise geometric measure. We study the problem with different measures: volume, diameter and radius. For volume, that is, the 1-norm of a cycle, two main results are presented. First, we prove that the problem is NP-hard to approximate within any constant factor. Second, we prove that for homology of dimension two or higher, the problem is NP-hard to approximate even when the Betti number is O(1). The latter result leads to the inapproximability of the problem of computing the nonbounding cycle with the smallest volume and computing cycles representing a homology basis with the minimal total volume. As for the other two measures defined by pairwise geodesic distance, diameter and radius, we show that the localization problem is NP-hard for diameter but is polynomial for radius. Our work is restricted to homology over the ℤ2 field.},
author = {Chen, Chao and Freedman, Daniel},
journal = {Discrete & Computational Geometry},
number = {3},
pages = {425 -- 448},
publisher = {Springer},
title = {{Hardness results for homology localization}},
doi = {10.1007/s00454-010-9322-8},
volume = {45},
year = {2011},
}
@article{3269,
abstract = {The unintentional scattering of light between neighboring surfaces in complex projection environments increases the brightness and decreases the contrast, disrupting the appearance of the desired imagery. To achieve satisfactory projection results, the inverse problem of global illumination must be solved to cancel this secondary scattering. In this paper, we propose a global illumination cancellation method that minimizes the perceptual difference between the desired imagery and the actual total illumination in the resulting physical environment. Using Gauss-Newton and active set methods, we design a fast solver for the bound constrained nonlinear least squares problem raised by the perceptual error metrics. Our solver is further accelerated with a CUDA implementation and multi-resolution method to achieve 1–2 fps for problems with approximately 3000 variables. We demonstrate the global illumination cancellation algorithm with our multi-projector system. Results show that our method preserves the color fidelity of the desired imagery significantly better than previous methods.},
author = {Sheng, Yu and Cutler, Barbara and Chen, Chao and Nasman, Joshua},
journal = {Computer Graphics Forum},
number = {4},
pages = {1261 -- 1268},
publisher = {Wiley-Blackwell},
title = {{Perceptual global illumination cancellation in complex projection environments}},
doi = {10.1111/j.1467-8659.2011.01985.x},
volume = {30},
year = {2011},
}
@inproceedings{3270,
abstract = {The persistence diagram of a filtered simplicial com- plex is usually computed by reducing the boundary matrix of the complex. We introduce a simple op- timization technique: by processing the simplices of the complex in decreasing dimension, we can “kill” columns (i.e., set them to zero) without reducing them. This technique completely avoids reduction on roughly half of the columns. We demonstrate that this idea significantly improves the running time of the reduction algorithm in practice. We also give an output-sensitive complexity analysis for the new al- gorithm which yields to sub-cubic asymptotic bounds under certain assumptions.},
author = {Chen, Chao and Kerber, Michael},
location = {Morschach, Switzerland},
pages = {197 -- 200},
publisher = {TU Dortmund},
title = {{Persistent homology computation with a twist}},
year = {2011},
}
@inbook{3271,
abstract = {In this paper we present an efficient framework for computation of persis- tent homology of cubical data in arbitrary dimensions. An existing algorithm using simplicial complexes is adapted to the setting of cubical complexes. The proposed approach enables efficient application of persistent homology in domains where the data is naturally given in a cubical form. By avoiding triangulation of the data, we significantly reduce the size of the complex. We also present a data-structure de- signed to compactly store and quickly manipulate cubical complexes. By means of numerical experiments, we show high speed and memory efficiency of our ap- proach. We compare our framework to other available implementations, showing its superiority. Finally, we report performance on selected 3D and 4D data-sets.},
author = {Wagner, Hubert and Chen, Chao and Vuçini, Erald},
booktitle = {Topological Methods in Data Analysis and Visualization II},
editor = {Peikert, Ronald and Hauser, Helwig and Carr, Hamish and Fuchs, Raphael},
pages = {91 -- 106},
publisher = {Springer},
title = {{Efficient computation of persistent homology for cubical data}},
doi = {10.1007/978-3-642-23175-9_7},
year = {2011},
}
@inbook{3311,
abstract = {Alpha shapes have been conceived in 1981 as an attempt to define the shape of a finite set of point in the plane. Since then, connections to diverse areas in the sciences and engineering have developed, including to pattern recognition, digital shape sampling and processing, and structural molecular biology. This survey begins with a historical account and discusses geometric, algorithmic, topological, and combinatorial aspects of alpha shapes in this sequence.},
author = {Herbert Edelsbrunner},
booktitle = {Tessellations in the Sciences},
publisher = {Springer},
title = {{Alpha shapes - a survey}},
year = {2011},
}
@misc{3312,
abstract = {We study the 3D reconstruction of plant roots from multiple 2D images. To meet the challenge caused by the delicate nature of thin branches, we make three innovations to cope with the sensitivity to image quality and calibration. First, we model the background as a harmonic function to improve the segmentation of the root in each 2D image. Second, we develop the concept of the regularized visual hull which reduces the effect of jittering and refraction by ensuring consistency with one 2D image. Third, we guarantee connectedness through adjustments to the 3D reconstruction that minimize global error. Our software is part of a biological phenotype/genotype study of agricultural root systems. It has been tested on more than 40 plant roots and results are promising in terms of reconstruction quality and efficiency.},
author = {Zheng, Ying and Gu, Steve and Edelsbrunner, Herbert and Tomasi, Carlo and Benfey, Philip},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision},
location = {Barcelona, Spain},
publisher = {IEEE},
title = {{Detailed reconstruction of 3D plant root shape}},
doi = {10.1109/ICCV.2011.6126475},
year = {2011},
}
@inproceedings{3313,
abstract = {Interpreting an image as a function on a compact sub- set of the Euclidean plane, we get its scale-space by diffu- sion, spreading the image over the entire plane. This gener- ates a 1-parameter family of functions alternatively defined as convolutions with a progressively wider Gaussian ker- nel. We prove that the corresponding 1-parameter family of persistence diagrams have norms that go rapidly to zero as time goes to infinity. This result rationalizes experimental observations about scale-space. We hope this will lead to targeted improvements of related computer vision methods.},
author = {Chen, Chao and Edelsbrunner, Herbert},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision},
location = {Barcelona, Spain},
publisher = {IEEE},
title = {{Diffusion runs low on persistence fast}},
doi = {10.1109/ICCV.2011.6126271},
year = {2011},
}
@inproceedings{3328,
abstract = {We report on a generic uni- and bivariate algebraic kernel that is publicly available with CGAL 3.7. It comprises complete, correct, though efficient state-of-the-art implementations on polynomials, roots of polynomial systems, and the support to analyze algebraic curves defined by bivariate polynomials. The kernel design is generic, that is, various number types and substeps can be exchanged. It is accompanied with a ready-to-use interface to enable arrangements induced by algebraic curves, that have already been used as basis for various geometric applications, as arrangements on Dupin cyclides or the triangulation of algebraic surfaces. We present two novel applications: arrangements of rotated algebraic curves and Boolean set operations on polygons bounded by segments of algebraic curves. We also provide experiments showing that our general implementation is competitive and even often clearly outperforms existing implementations that are explicitly tailored for specific types of non-linear curves that are available in CGAL.},
author = {Berberich, Eric and Hemmer, Michael and Kerber, Michael},
location = {Paris, France},
pages = {179 -- 186},
publisher = {ACM},
title = {{A generic algebraic kernel for non linear geometric applications}},
doi = {10.1145/1998196.1998224},
year = {2011},
}
@inproceedings{3329,
abstract = {We consider the offset-deconstruction problem: Given a polygonal shape Q with n vertices, can it be expressed, up to a tolerance µ in Hausdorff distance, as the Minkowski sum of another polygonal shape P with a disk of fixed radius? If it does, we also seek a preferably simple-looking solution shape P; then, P's offset constitutes an accurate, vertex-reduced, and smoothened approximation of Q. We give an O(n log n)-time exact decision algorithm that handles any polygonal shape, assuming the real-RAM model of computation. An alternative algorithm, based purely on rational arithmetic, answers the same deconstruction problem, up to an uncertainty parameter, and its running time depends on the parameter δ (in addition to the other input parameters: n, δ and the radius of the disk). If the input shape is found to be approximable, the rational-arithmetic algorithm also computes an approximate solution shape for the problem. For convex shapes, the complexity of the exact decision algorithm drops to O(n), which is also the time required to compute a solution shape P with at most one more vertex than a vertex-minimal one. Our study is motivated by applications from two different domains. However, since the offset operation has numerous uses, we anticipate that the reverse question that we study here will be still more broadly applicable. We present results obtained with our implementation of the rational-arithmetic algorithm.},
author = {Berberich, Eric and Halperin, Dan and Kerber, Michael and Pogalnikova, Roza},
booktitle = {Proceedings of the twenty-seventh annual symposium on Computational geometry},
location = {Paris, France},
pages = {187 -- 196},
publisher = {ACM},
title = {{Deconstructing approximate offsets}},
doi = {10.1145/1998196.1998225},
year = {2011},
}