A SEGMENTATION METHOD FOR 3D MESHES OF HISTORIC BUILDINGS

[EN] In this article, a method for 3D mesh segmentation focused on the representation of historic buildings is proposed. This type of buildings are characterized by having singularities and characteristic elements in the facades.The main objective is to recognize these features in the buildings, understanding features as those parts of the model that differ from the main structure of the building, such as doors or windows. The idea is to use a recognition algorithm of flat faces allowing to create a graph that reflects the shape of the three-dimensional model. At a later step, this graph will be matched against some pre-defined graphs that will represent the patterns to look for.[ES] En este artículo se propone un método de segmentación de mallas 3D enfocado a representaciones de edificios históricos.Este tipo de edificios se caracterizan por tener singularidades y elementos caracteristicos en las fachadas. El objetivo principal consiste en reconocer estas características en los edificios, entendiéndose como características aquellas partes del modelo que difieren de la estructura principal del edificio, tales como puertas o ventanas. La idea es utilizar un algoritmo de reconocimiento de caras planas que permita crear un grafo que refleje la forma del modelo tridimensional. En una etapa posterior, este grafo se comparará con grafos predefinidos que conformaran los patrones a buscar.Herráez, BJ.; Vendrell Vidal, E. (2016). UN PROCEDIMIENTO DE SEGMENTACIÓN DE MALLAS 3D DE EDIFICIOS HISTÓRICOS. En 8th International congress on archaeology, computer graphics, cultural heritage and innovation. Editorial Universitat Politècnica de València. 311-313. https://doi.org/10.4995/arqueologica8.2016.3524OCS31131

Shape measure for identifying perceptually informative parts of 3d objects

We propose a mathematical approach for quantifying shape complexity of 3D surfaces based on perceptual principles of visual saliency. Our curvature variation measure (CVM), as a 3D feature, combines surface curvature and information theory by leveraging bandwidth-optimized kernel density estimators. Using a part decomposition algorithm for digitized 3D objects, represented as triangle meshes, we apply our shape measure to transform the low level mesh representation into a perceptually informative form. Further, we analyze the effects of noise, sensitivity to digitization, occlusions, and descriptiveness to demonstrate our shape measure on laser-scanned real world 3D objects. 1

Segmentation hiérarchique de maillage 3D à partir des dynamiques de contour

La segmentation de maillage 3D est un problème fondamental en synthèse d'image et est devenu un enjeu important pour de nombreuses applications. Cet article introduit une nouvelle méthode de segmentation hiérarchique basée sur la ligne de partage des eaux (LPE), les cascades et les dynamiques de contour. La LPE génère une première partition composée de petits patchs surfaciques ; les dynamiques de contour offrent une bonne caractérisation des frontières et les cascades mettent à disposition plusieurs niveaux de segmentation pour l'utilisateur. Le procédé de fusion hiérarchique basé sur les cascades génère un arbre qui contient plusieurs schémas de segmentation ; l'utilisateur a ainsi la possibilité de parcourir facilement chacun des niveaux de segmentation contenus dans cet arbre pour sélectionner le plus adapté à son application

DETC2008-49438 IDENTIFYING FEATURE HANDLES OF FREEFORM SHAPES

ABSTRACT Trends, ergonomics and engineering analysis post more challenges than ever to product shape designs, especially in the freeform area. In this paper, freeform feature handles are proposed for easing of difficulties in modifying an existing freeform shape. Considering the variations of curvature as the footprint of a freeform feature(s), curvature analysis is applied to find manipulators, e.g. handles, of a freeform feature(s) in the shape. For these, a Laplacian based pre-processing tool is proposed first to eliminate background noise of the shape. Then least square conformal mapping is applied to map the 3D geometry to a 2D polygon mesh with the minimum distortions of angle deformation and non-uniform scaling. By mapping the curvature of each vertex in the 3D shape to the 2D polygon mesh, a curvature raster image is created. With image processing tools, different levels of curvature changing are identified and marked as feature point(s) / line(s) / area(s) in the freeform shape. Following the definitions, the handles for those intrinsic freeform features are established by the user based on those feature items. Experiments were conducted on different types of shapes to verify the rightness of the proposed method. Different effects caused by different parameters are discussed as well

Semantic Segmentation of 3D Textured Meshes for Urban Scene Analysis

International audienceClassifying 3D measurement data has become a core problem in photogram-metry and 3D computer vision, since the rise of modern multiview geometry techniques, combined with affordable range sensors. We introduce a Markov Random Field-based approach for segmenting textured meshes generated via multi-view stereo into urban classes of interest. The input mesh is first partitioned into small clusters, referred to as superfacets, from which geometric and photometric features are computed. A random forest is then trained to predict the class of each superfacet as well as its similarity with the neighboring superfacets. Similarity is used to assign the weights of the Markov Random Field pairwise-potential and accounts for contextual information between the classes. The experimental results illustrate the efficacy and accuracy of the proposed framework

3D mesh segmentation of historic buildings for architectural surveys

[EN] Advances in three-dimensional (3D) acquisition systems have introduced this technology to more fields of study, such as archaeology or architecture. In the architectural field, scanning a building is one of the first possible steps from which a 3D model can be obtained and can be later used for visualisation and/or feature analysis, thanks to computer-based pattern recognition tools. The automation of these tools allows for temporal savings and has become a strong aid for professionals, so that more and more methods are developed with this objective. In this article, a method for 3D mesh segmentation focused on the representation of historic buildings is proposed. This type of buildings is characterised by having singularities and features in façades, such as doors or windows. The main objective is to recognise these features, understanding them as those parts of the model that differ from the main structure of the building. The idea is to use a recognition algorithm for planar faces that allows users to create a graph showing the connectivity between them, therefore allowing the reflection of the shape of the 3Dmodel. At a later step, this graph is matched against some pre-defined graphs that represent the patterns to look for. Each coincidence between both graphs indicate the position of one of the characteristics sought. The developed method has proved to be effective for feature detection and suitable for inclusion in architectural surveying applications.[ES] Los avances en los sistemas de adquisición tridimensionales (3D) han provocado que este tipo de tecnología se introduzca en cada vez más campos de estudio, como son la arqueología o la arquitectura. En el campo arquitectónico el escaneado de edificios constituye el primer paso con el que se obtienen modelos 3Dque más tarde, pueden ser utilizados para la visualización y/o análisis de las características de los mismos edificios, gracias a herramientas informáticas de reconocimiento de patrones. La automatización de estas herramientas permite un ahorro temporal y supone una ayuda a los profesionales, por lo que cada vez más métodos se desarrollan con este objetivo. En este artículo se propone un método de segmentación de mallas 3D enfocado a la representación de edificios históricos. Este tipo de edificios se caracterizan por tener singularidades y elementos característicos en las fachadas, tales como puertas o ventanas. El objetivo principal consiste en reconocer estas características en los edificios, entendiéndose como tales aquellas partes del modelo que difieren de la estructura principal del mismo. La idea es utilizar un algoritmo de reconocimiento de caras planas que permita crear un grafo que muestre la conectividad entre ellas y que por tanto refleje la forma del modelo tridimensional. En una etapa posterior, este grafo se compara con grafos predefinidos que conforman los patrones a buscar. Cada coincidencia entre ambos grafos indica la posición de una de las características buscadas. El método desarrollado ha resultado ser eficaz para la detección de características y adecuado para su inclusión en aplicaciones de levantamiento arquitectónico.Este trabajo se ha realizado parcialmente en el marco del proyecto de investigación “R4FA. Desarrollo de un Sistema Integrado de Restauracion, Recomposicion, Restitucion y Representacion de Fragmentos Arqueologicos” (HAR2015-69408-R), financiado por el Programa Estatal de Investigación, Desarrollo e Innovación Orientada a los Retos de la Sociedad, Convocatoria 2015, Modalidad 1: «Proyectos de I+D+I».Herráez, BJ.; Vendrell, E. (2018). Segmentación de mallas 3D de edificios históricos para levantamiento arquitectónico. Virtual Archaeology Review. 9(18):66-76. https://doi.org/10.4995/var.2018.5858SWORD667691