TY - JOUR AB - 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. AU - Sheng, Yu AU - Cutler, Barbara AU - Chen, Chao AU - Nasman, Joshua ID - 3269 IS - 4 JF - Computer Graphics Forum TI - Perceptual global illumination cancellation in complex projection environments VL - 30 ER - TY - JOUR AB - 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. AU - Chen, Chao AU - Freedman, Daniel ID - 3267 IS - 3 JF - Discrete & Computational Geometry TI - Hardness results for homology localization VL - 45 ER - TY - CHAP AB - We study the topology of the Megaparsec Cosmic Web in terms of the scale-dependent Betti numbers, which formalize the topological information content of the cosmic mass distribution. While the Betti numbers do not fully quantify topology, they extend the information beyond conventional cosmological studies of topology in terms of genus and Euler characteristic. The richer information content of Betti numbers goes along the availability of fast algorithms to compute them. For continuous density fields, we determine the scale-dependence of Betti numbers by invoking the cosmologically familiar filtration of sublevel or superlevel sets defined by density thresholds. For the discrete galaxy distribution, however, the analysis is based on the alpha shapes of the particles. These simplicial complexes constitute an ordered sequence of nested subsets of the Delaunay tessellation, a filtration defined by the scale parameter, α. As they are homotopy equivalent to the sublevel sets of the distance field, they are an excellent tool for assessing the topological structure of a discrete point distribution. In order to develop an intuitive understanding for the behavior of Betti numbers as a function of α, and their relation to the morphological patterns in the Cosmic Web, we first study them within the context of simple heuristic Voronoi clustering models. These can be tuned to consist of specific morphological elements of the Cosmic Web, i.e. clusters, filaments, or sheets. To elucidate the relative prominence of the various Betti numbers in different stages of morphological evolution, we introduce the concept of alpha tracks. Subsequently, we address the topology of structures emerging in the standard LCDM scenario and in cosmological scenarios with alternative dark energy content. The evolution of the Betti numbers is shown to reflect the hierarchical evolution of the Cosmic Web. We also demonstrate that the scale-dependence of the Betti numbers yields a promising measure of cosmological parameters, with a potential to help in determining the nature of dark energy and to probe primordial non-Gaussianities. We also discuss the expected Betti numbers as a function of the density threshold for superlevel sets of a Gaussian random field. Finally, we introduce the concept of persistent homology. It measures scale levels of the mass distribution and allows us to separate small from large scale features. Within the context of the hierarchical cosmic structure formation, persistence provides a natural formalism for a multiscale topology study of the Cosmic Web. AU - Van De Weygaert, Rien AU - Vegter, Gert AU - Edelsbrunner, Herbert AU - Jones, Bernard AU - Pranav, Pratyush AU - Park, Changbom AU - Hellwing, Wojciech AU - Eldering, Bob AU - Kruithof, Nico AU - Bos, Patrick AU - Hidding, Johan AU - Feldbrugge, Job AU - Ten Have, Eline AU - Van Engelen, Matti AU - Caroli, Manuel AU - Teillaud, Monique ED - Gavrilova, Marina ED - Tan, Kenneth ED - Mostafavi, Mir ID - 3335 T2 - Transactions on Computational Science XIV TI - Alpha, Betti and the Megaparsec Universe: On the topology of the Cosmic Web VL - 6970 ER - TY - CONF AB - 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. AU - Berberich, Eric AU - Halperin, Dan AU - Kerber, Michael AU - Pogalnikova, Roza ID - 3329 T2 - Proceedings of the twenty-seventh annual symposium on Computational geometry TI - Deconstructing approximate offsets ER - TY - JOUR AB - Given an algebraic hypersurface O in ℝd, how many simplices are necessary for a simplicial complex isotopic to O? We address this problem and the variant where all vertices of the complex must lie on O. We give asymptotically tight worst-case bounds for algebraic plane curves. Our results gradually improve known bounds in higher dimensions; however, the question for tight bounds remains unsolved for d ≥ 3. AU - Kerber, Michael AU - Sagraloff, Michael ID - 3332 IS - 3 JF - Graphs and Combinatorics TI - A note on the complexity of real algebraic hypersurfaces VL - 27 ER - TY - CONF AB - We consider the problem of approximating all real roots of a square-free polynomial f. Given isolating intervals, our algorithm refines each of them to a width at most 2-L, that is, each of the roots is approximated to L bits after the binary point. Our method provides a certified answer for arbitrary real polynomials, only requiring finite approximations of the polynomial coefficient and choosing a suitable working precision adaptively. In this way, we get a correct algorithm that is simple to implement and practically efficient. Our algorithm uses the quadratic interval refinement method; we adapt that method to be able to cope with inaccuracies when evaluating f, without sacrificing its quadratic convergence behavior. We prove a bound on the bit complexity of our algorithm in terms of degree, coefficient size and discriminant. Our bound improves previous work on integer polynomials by a factor of deg f and essentially matches best known theoretical bounds on root approximation which are obtained by very sophisticated algorithms. AU - Kerber, Michael AU - Sagraloff, Michael ID - 3330 TI - Root refinement for real polynomials ER - TY - CONF AB - 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. AU - Berberich, Eric AU - Hemmer, Michael AU - Kerber, Michael ID - 3328 TI - A generic algebraic kernel for non linear geometric applications ER - TY - JOUR AU - Edelsbrunner, Herbert AU - Pach, János AU - Ziegler, Günter ID - 3334 IS - 1 JF - Discrete & Computational Geometry TI - Letter from the new editors-in-chief VL - 45 ER - TY - CONF AB - In this paper, we present the first output-sensitive algorithm to compute the persistence diagram of a filtered simplicial complex. For any Γ>0, it returns only those homology classes with persistence at least Γ. Instead of the classical reduction via column operations, our algorithm performs rank computations on submatrices of the boundary matrix. For an arbitrary constant δ ∈ (0,1), the running time is O(C(1-δ)ΓR(n)log n), where C(1-δ)Γ is the number of homology classes with persistence at least (1-δ)Γ, n is the total number of simplices, and R(n) is the complexity of computing the rank of an n x n matrix with O(n) nonzero entries. Depending on the choice of the rank algorithm, this yields a deterministic O(C(1-δ)Γn2.376) algorithm, a O(C(1-δ)Γn2.28) Las-Vegas algorithm, or a O(C(1-δ)Γn2+ε) Monte-Carlo algorithm for an arbitrary ε>0. AU - Chen, Chao AU - Kerber, Michael ID - 3367 TI - An output sensitive algorithm for persistent homology ER - TY - JOUR AB - 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. AU - Fasy, Brittany Terese ID - 3781 IS - 1-2 JF - Acta Sci. Math. (Szeged) TI - The difference in length of curves in R^n VL - 77 ER - TY - CHAP AB - 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. AU - Edelsbrunner, Herbert AU - Kerber, Michael ED - Calude, Cristian ED - Rozenberg, Grzegorz ED - Salomaa, Arto ID - 3796 T2 - Rainbow of Computer Science TI - Covering and packing with spheres by diagonal distortion in R^n VL - 6570 ER - TY - JOUR AB - 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. AU - Wang, Bei AU - Edelsbrunner, Herbert AU - Morozov, Dmitriy ID - 3965 IS - 2.2 JF - Journal of Experimental Algorithmics TI - Computing elevation maxima by searching the Gauss sphere VL - 16 ER - TY - CHAP AB - 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. AU - Wagner, Hubert AU - Chen, Chao AU - Vuçini, Erald ED - Peikert, Ronald ED - Hauser, Helwig ED - Carr, Hamish ED - Fuchs, Raphael ID - 3271 T2 - Topological Methods in Data Analysis and Visualization II TI - Efficient computation of persistent homology for cubical data ER - TY - CONF AB - 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. AU - Chen, Chao AU - Kerber, Michael ID - 3270 TI - Persistent homology computation with a twist ER - TY - GEN AB - 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. AU - Zheng, Ying AU - Gu, Steve AU - Edelsbrunner, Herbert AU - Tomasi, Carlo AU - Benfey, Philip ID - 3312 T2 - Proceedings of the IEEE International Conference on Computer Vision TI - Detailed reconstruction of 3D plant root shape ER - TY - CONF AB - 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. AU - Chen, Chao AU - Edelsbrunner, Herbert ID - 3313 T2 - Proceedings of the IEEE International Conference on Computer Vision TI - Diffusion runs low on persistence fast ER - TY - CHAP AB - 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. AU - Edelsbrunner, Herbert ED - van de Weygaert, R ED - Vegter, G ED - Ritzerveld, J ED - Icke, V ID - 3311 T2 - Tessellations in the Sciences: Virtues, Techniques and Applications of Geometric Tilings TI - Alpha shapes - a survey ER - TY - JOUR AB - By definition, transverse intersections are stable under in- finitesimal perturbations. Using persistent homology, we ex- tend this notion to sizeable perturbations. Specifically, we assign to each homology class of the intersection its robust- ness, the magnitude of a perturbation necessary to kill it, and prove that robustness is stable. Among the applications of this result is a stable notion of robustness for fixed points of continuous mappings and a statement of stability for con- tours of smooth mappings. AU - Edelsbrunner, Herbert AU - Morozov, Dmitriy AU - Patel, Amit ID - 3377 IS - 3 JF - Foundations of Computational Mathematics TI - Quantifying transversality by measuring the robustness of intersections VL - 11 ER - TY - JOUR AB - The theory of intersection homology was developed to study the singularities of a topologically stratified space. This paper in- corporates this theory into the already developed framework of persistent homology. We demonstrate that persistent intersec- tion homology gives useful information about the relationship between an embedded stratified space and its singularities. We give, and prove the correctness of, an algorithm for the computa- tion of the persistent intersection homology groups of a filtered simplicial complex equipped with a stratification by subcom- plexes. We also derive, from Poincare ́ Duality, some structural results about persistent intersection homology. AU - Bendich, Paul AU - Harer, John ID - 3378 IS - 3 JF - Foundations of Computational Mathematics TI - Persistent intersection homology VL - 11 ER - TY - CONF AB - We introduce TopoCut: a new way to integrate knowledge about topological properties (TPs) into random field image segmentation model. Instead of including TPs as additional constraints during minimization of the energy function, we devise an efficient algorithm for modifying the unary potentials such that the resulting segmentation is guaranteed with the desired properties. Our method is more flexible in the sense that it handles more topology constraints than previous methods, which were only able to enforce pairwise or global connectivity. In particular, our method is very fast, making it for the first time possible to enforce global topological properties in practical image segmentation tasks. AU - Chen, Chao AU - Freedman, Daniel AU - Lampert, Christoph ID - 3336 SN - 978-1-4577-0394-2 T2 - CVPR: Computer Vision and Pattern Recognition TI - Enforcing topological constraints in random field image segmentation ER - TY - CONF AB - In this paper, we establish a correspondence between the incremental algorithm for computing AT-models [8,9] and the one for computing persistent homology [6,14,15]. We also present a decremental algorithm for computing AT-models that allows to extend the persistence computation to a wider setting. Finally, we show how to combine incremental and decremental techniques for persistent homology computation. AU - Gonzalez-Diaz, Rocio AU - Ion, Adrian AU - Jimenez, Maria Jose AU - Poyatos, Regina ID - 9648 SN - 03029743 T2 - Computer Analysis of Images and Patterns TI - Incremental-decremental algorithm for computing AT-models and persistent homology VL - 6854 ER - TY - CONF AB - This paper presents a method to create a model of an articulated object using the planar motion in an initialization video. The model consists of rigid parts connected by points of articulation. The rigid parts are described by the positions of salient feature-points tracked throughout the video. Following a filtering step that identifies points that belong to different objects, rigid parts are found by a grouping process in a graph pyramid. Valid articulation points are selected by verifying multiple hypotheses for each pair of parts. AU - Artner, Nicole M. AU - Ion, Adrian AU - Kropatsch, Walter G. ED - Jiang, Xiaoyi ED - Ferrer, Miquel ED - Torsello, Andrea ID - 10907 SN - 0302-9743 T2 - Graph-Based Representations in Pattern Recognition TI - Spatio-temporal extraction of articulated models in a graph pyramid VL - 6658 ER - TY - CONF AB - We address the problem of localizing homology classes, namely, finding the cycle representing a given class with the most concise geometric measure. We focus on the volume measure, that is, the 1-norm of a cycle. Two main results are presented. First, we prove 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). A side effect is 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. We also discuss other geometric measures (diameter and radius) and show their disadvantages in homology localization. Our work is restricted to homology over the ℤ2 field. AU - Chen, Chao AU - Freedman, Daniel ID - 10909 T2 - Proceedings of the 2010 Annual ACM-SIAM Symposium on Discrete Algorithms TI - Hardness results for homology localization ER - TY - CONF AB - In cortex surface segmentation, the extracted surface is required to have a particular topology, namely, a two-sphere. We present a new method for removing topology noise of a curve or surface within the level set framework, and thus produce a cortical surface with correct topology. We define a new energy term which quantifies topology noise. We then show how to minimize this term by computing its functional derivative with respect to the level set function. This method differs from existing methods in that it is inherently continuous and not digital; and in the way that our energy directly relates to the topology of the underlying curve or surface, versus existing knot-based measures which are related in a more indirect fashion. The proposed flow is validated empirically. AU - Chen, Chao AU - Freedman, Daniel ID - 3782 T2 - Conference proceedings MCV 2010 TI - Topology noise removal for curve and surface evolution VL - 6533 ER - TY - CHAP AB - The (apparent) contour of a smooth mapping from a 2-manifold to the plane, f: M → R2 , is the set of critical values, that is, the image of the points at which the gradients of the two component functions are linearly dependent. Assuming M is compact and orientable and measuring difference with the erosion distance, we prove that the contour is stable. AU - Edelsbrunner, Herbert AU - Morozov, Dmitriy AU - Patel, Amit ID - 3795 T2 - Topological Data Analysis and Visualization: Theory, Algorithms and Applications TI - The stability of the apparent contour of an orientable 2-manifold ER - TY - CONF AB - We define the robustness of a level set homology class of a function f:XR as the magnitude of a perturbation necessary to kill the class. Casting this notion into a group theoretic framework, we compute the robustness for each class, using a connection to extended persistent homology. The special case X=R3 has ramifications in medical imaging and scientific visualization. AU - Bendich, Paul AU - Edelsbrunner, Herbert AU - Morozov, Dmitriy AU - Patel, Amit ID - 3848 TI - The robustness of level sets VL - 6346 ER - TY - CONF AB - Quantitative languages are an extension of boolean languages that assign to each word a real number. Mean-payoff automata are finite automata with numerical weights on transitions that assign to each infinite path the long-run average of the transition weights. When the mode of branching of the automaton is deterministic, nondeterministic, or alternating, the corresponding class of quantitative languages is not robust as it is not closed under the pointwise operations of max, min, sum, and numerical complement. Nondeterministic and alternating mean-payoff automata are not decidable either, as the quantitative generalization of the problems of universality and language inclusion is undecidable. We introduce a new class of quantitative languages, defined by mean-payoff automaton expressions, which is robust and decidable: it is closed under the four pointwise operations, and we show that all decision problems are decidable for this class. Mean-payoff automaton expressions subsume deterministic meanpayoff automata, and we show that they have expressive power incomparable to nondeterministic and alternating mean-payoff automata. We also present for the first time an algorithm to compute distance between two quantitative languages, and in our case the quantitative languages are given as mean-payoff automaton expressions. AU - Chatterjee, Krishnendu AU - Doyen, Laurent AU - Edelsbrunner, Herbert AU - Henzinger, Thomas A AU - Rannou, Philippe ID - 3853 TI - Mean-payoff automaton expressions VL - 6269 ER - TY - CONF AB - Using ideas from persistent homology, the robustness of a level set of a real-valued function is defined in terms of the magnitude of the perturbation necessary to kill the classes. Prior work has shown that the homology and robustness information can be read off the extended persistence diagram of the function. This paper extends these results to a non-uniform error model in which perturbations vary in their magnitude across the domain. AU - Bendich, Paul AU - Edelsbrunner, Herbert AU - Kerber, Michael AU - Patel, Amit ID - 3849 TI - Persistent homology under non-uniform error VL - 6281 ER - TY - CONF AB - Given a polygonal shape Q with n vertices, can it be expressed, up to a tolerance ε in Hausdorff distance, as the Minkowski sum of another polygonal shape with a disk of fixed radius? If it does, we also seek a preferably simple solution shape P;P’s offset constitutes an accurate, vertex-reduced, and smoothened approximation of Q. We give a decision algorithm for fixed radius in O(nlogn) time that handles any polygonal shape. For convex shapes, the complexity 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. AU - Berberich, Eric AU - Halperin, Dan AU - Kerber, Michael AU - Pogalnikova, Roza ID - 3850 TI - Polygonal reconstruction from approximate offsets ER - TY - JOUR AB - We are interested in 3-dimensional images given as arrays of voxels with intensity values. Extending these values to acontinuous function, we study the robustness of homology classes in its level and interlevel sets, that is, the amount of perturbationneeded to destroy these classes. The structure of the homology classes and their robustness, over all level and interlevel sets, can bevisualized by a triangular diagram of dots obtained by computing the extended persistence of the function. We give a fast hierarchicalalgorithm using the dual complexes of oct-tree approximations of the function. In addition, we show that for balanced oct-trees, thedual complexes are geometrically realized in $R^3$ and can thus be used to construct level and interlevel sets. We apply these tools tostudy 3-dimensional images of plant root systems. AU - Bendich, Paul AU - Edelsbrunner, Herbert AU - Kerber, Michael ID - 3901 IS - 6 JF - IEEE Transactions of Visualization and Computer Graphics TI - Computing robustness and persistence for images VL - 16 ER - TY - CONF AB - We describe an algorithm for segmenting three-dimensional medical imaging data modeled as a continuous function on a 3-manifold. It is related to watershed algorithms developed in image processing but is closer to its mathematical roots, which are Morse theory and homological algebra. It allows for the implicit treatment of an underlying mesh, thus combining the structural integrity of its mathematical foundations with the computational efficiency of image processing. AU - Edelsbrunner, Herbert AU - Harer, John ID - 3968 TI - The persistent Morse complex segmentation of a 3-manifold VL - 5903 ER -