Fitting Parabolas in Noisy Images

A novel approach to fitting parabolas to scattered data is introduced by putting special emphasis on the robustness of the approach. The robust fit is achieved by not taking into account a proportion of the “most outlying” observations, allowing the procedure to trim them off. The most outlying observations are self-determined by the data. Procrustes analysis techniques and a particular type of “concentration” steps are the keystone of the proposed methodology. An application to a retinographic study is also presented

Minkowski Sum Construction and other Applications of Arrangements of Geodesic Arcs on the Sphere

We present two exact implementations of efficient output-sensitive algorithms that compute Minkowski sums of two convex polyhedra in 3D. We do not assume general position. Namely, we handle degenerate input, and produce exact results. We provide a tight bound on the exact maximum complexity of Minkowski sums of polytopes in 3D in terms of the number of facets of the summand polytopes. The algorithms employ variants of a data structure that represents arrangements embedded on two-dimensional parametric surfaces in 3D, and they make use of many operations applied to arrangements in these representations. We have developed software components that support the arrangement data-structure variants and the operations applied to them. These software components are generic, as they can be instantiated with any number type. However, our algorithms require only (exact) rational arithmetic. These software components together with exact rational-arithmetic enable a robust, efficient, and elegant implementation of the Minkowski-sum constructions and the related applications. These software components are provided through a package of the Computational Geometry Algorithm Library (CGAL) called Arrangement_on_surface_2. We also present exact implementations of other applications that exploit arrangements of arcs of great circles embedded on the sphere. We use them as basic blocks in an exact implementation of an efficient algorithm that partitions an assembly of polyhedra in 3D with two hands using infinite translations. This application distinctly shows the importance of exact computation, as imprecise computation might result with dismissal of valid partitioning-motions.Comment: A Ph.D. thesis carried out at the Tel-Aviv university. 134 pages long. The advisor was Prof. Dan Halperi

Computing the exact arrangement of circles on a sphere, with applications in structural biology

revision de la version de Decembre 2006Given a collection of circles on a sphere, we adapt the Bentley-Ottmann algorithm to the spherical setting to compute the {\em exact} arrangement of the circles. The algorithm consists of sweeping the sphere with a meridian, which is non trivial because of the degenerate cases and the algebraic specification of event points. From an algorithmic perspective, and with respect to general sweep-line algorithms, we investigate a strategy maintaining a linear size event queue. (The algebraic aspects involved in the development of the predicates involved in our algorithm are reported in a companion paper.) From an implementation perspective, we present the first effective arrangement calculation dealing with general circles on a sphere in an exact fashion, as exactness incurs a mere factor of two with respect to calculations performed using {\em double} floating point numbers on generic examples. In particular, we stress the importance of maintaining a linear size queue, in conjunction with arithmetic filter failures. From an application perspective, we present an application in structural biology. Given a collection of atomic balls, we adapt the sweep-line algorithm to report all balls covering a given face of the spherical arrangement on a given atom. This calculation is used to define molecular surface related quantities going beyond the classical exposed and buried solvent accessible surface areas. Spectacular differences w.r.t. traditional observations on protein - protein and protein - drug complexes are also reported

Extracting geometric information from images with the novel Self Affine Feature Transform

Based on our research, the Self Affine Feature Transform (SAFT) was introduced as it extracts quantities which hold information of the edges in the investigated image region. This paper gives details on algorithms which extract various geometric information from the SAFT matrix. As different image types should be analysed differently, a classification procedure must be performed first. The main contribution of this paper is to describe this classification in details. Information extraction is applied for solving different 2-dimensional image processing tasks, amongst them the detection of con­ver­gent lines, circles, ellipses, parabolae and hiperbolae or localizing corners of calibration grids in a robust and accurate manner

Collection of abstracts of the 24th European Workshop on Computational Geometry

International audienceThe 24th European Workshop on Computational Geomety (EuroCG'08) was held at INRIA Nancy - Grand Est & LORIA on March 18-20, 2008. The present collection of abstracts contains the 63 scientific contributions as well as three invited talks presented at the workshop

Active shape models with focus on overlapping problems applied to plant detection and soil pore analysis

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F-formation Detection: Individuating Free-standing Conversational Groups in Images

Detection of groups of interacting people is a very interesting and useful task in many modern technologies, with application fields spanning from video-surveillance to social robotics. In this paper we first furnish a rigorous definition of group considering the background of the social sciences: this allows us to specify many kinds of group, so far neglected in the Computer Vision literature. On top of this taxonomy, we present a detailed state of the art on the group detection algorithms. Then, as a main contribution, we present a brand new method for the automatic detection of groups in still images, which is based on a graph-cuts framework for clustering individuals; in particular we are able to codify in a computational sense the sociological definition of F-formation, that is very useful to encode a group having only proxemic information: position and orientation of people. We call the proposed method Graph-Cuts for F-formation (GCFF). We show how GCFF definitely outperforms all the state of the art methods in terms of different accuracy measures (some of them are brand new), demonstrating also a strong robustness to noise and versatility in recognizing groups of various cardinality.Comment: 32 pages, submitted to PLOS On

Detection and identification of elliptical structure arrangements in images: theory and algorithms

Cette thèse porte sur différentes problématiques liées à la détection, l'ajustement et l'identification de structures elliptiques en images. Nous plaçons la détection de primitives géométriques dans le cadre statistique des méthodes a contrario afin d'obtenir un détecteur de segments de droites et d'arcs circulaires/elliptiques sans paramètres et capable de contrôler le nombre de fausses détections. Pour améliorer la précision des primitives détectées, une technique analytique simple d'ajustement de coniques est proposée ; elle combine la distance algébrique et l'orientation du gradient. L'identification d'une configuration de cercles coplanaires en images par une signature discriminante demande normalement la rectification Euclidienne du plan contenant les cercles. Nous proposons une technique efficace de calcul de la signature qui s'affranchit de l'étape de rectification ; elle est fondée exclusivement sur des propriétés invariantes du plan projectif, devenant elle même projectivement invariante. ABSTRACT : This thesis deals with different aspects concerning the detection, fitting, and identification of elliptical features in digital images. We put the geometric feature detection in the a contrario statistical framework in order to obtain a combined parameter-free line segment, circular/elliptical arc detector, which controls the number of false detections. To improve the accuracy of the detected features, especially in cases of occluded circles/ellipses, a simple closed-form technique for conic fitting is introduced, which merges efficiently the algebraic distance with the gradient orientation. Identifying a configuration of coplanar circles in images through a discriminant signature usually requires the Euclidean reconstruction of the plane containing the circles. We propose an efficient signature computation method that bypasses the Euclidean reconstruction; it relies exclusively on invariant properties of the projective plane, being thus itself invariant under perspective