Data-Driven Shape Analysis and Processing

Data-driven methods play an increasingly important role in discovering geometric, structural, and semantic relationships between 3D shapes in collections, and applying this analysis to support intelligent modeling, editing, and visualization of geometric data. In contrast to traditional approaches, a key feature of data-driven approaches is that they aggregate information from a collection of shapes to improve the analysis and processing of individual shapes. In addition, they are able to learn models that reason about properties and relationships of shapes without relying on hard-coded rules or explicitly programmed instructions. We provide an overview of the main concepts and components of these techniques, and discuss their application to shape classification, segmentation, matching, reconstruction, modeling and exploration, as well as scene analysis and synthesis, through reviewing the literature and relating the existing works with both qualitative and numerical comparisons. We conclude our report with ideas that can inspire future research in data-driven shape analysis and processing.Comment: 10 pages, 19 figure

Geometric constraint subsets and subgraphs in the analysis of assemblies and mechanisms

Geometric Reasoning ability is central to many applications in CAD/CAM/CAPP environments -- An increasing demand exists for Geometric Reasoning systems which evaluate the feasibility of virtual scenes specified by geometric relations -- Thus, the Geometric Constraint Satisfaction or Scene Feasibility (GCS/SF) problem consists of a basic scenario containing geometric entities, whose context is used to propose constraining relations among still undefined entities -- If the constraint specification is consistent, the answer of the problem is one of finitely or infinitely many solution scenarios satisfying the prescribed constraints -- Otherwise, a diagnostic of inconsistency is expected -- The three main approaches used for this problem are numerical, procedural or operational and mathematical -- Numerical and procedural approaches answer only part of the problem, and are not complete in the sense that a failure to provide an answer does not preclude the existence of one -- The mathematical approach previously presented by the authors describes the problem using a set of polynomial equations -- The common roots to this set of polynomials characterizes the solution space for such a problem -- That work presents the use of Groebner basis techniques for verifying the consistency of the constraints -- It also integrates subgroups of the Special Euclidean Group of Displacements SE(3) in the problem formulation to exploit the structure implied by geometric relations -- Although theoretically sound, these techniques require large amounts of computing resources -- This work proposes Divide-and-Conquer techniques applied to local GCS/SF subproblems to identify strongly constrained clusters of geometric entities -- The identification and preprocessing of these clusters generally reduces the effort required in solving the overall problem -- Cluster identification can be related to identifying short cycles in the Spatial Con straint graph for the GCS/SF problem -- Their preprocessing uses the aforementioned Algebraic Geometry and Group theoretical techniques on the local GCS/SF problems that correspond to these cycles -- Besides improving theefficiency of the solution approach, the Divide-and-Conquer techniques capture the physical essence of the problem -- This is illustrated by applying the discussed techniques to the analysis of the degrees of freedom of mechanism

Inferring Latent States and Refining Force Estimates via Hierarchical Dirichlet Process Modeling in Single Particle Tracking Experiments

Optical microscopy provides rich spatio-temporal information characterizing in vivo molecular motion. However, effective forces and other parameters used to summarize molecular motion change over time in live cells due to latent state changes, e.g., changes induced by dynamic micro-environments, photobleaching, and other heterogeneity inherent in biological processes. This study focuses on techniques for analyzing Single Particle Tracking (SPT) data experiencing abrupt state changes. We demonstrate the approach on GFP tagged chromatids experiencing metaphase in yeast cells and probe the effective forces resulting from dynamic interactions that reflect the sum of a number of physical phenomena. State changes are induced by factors such as microtubule dynamics exerting force through the centromere, thermal polymer fluctuations, etc. Simulations are used to demonstrate the relevance of the approach in more general SPT data analyses. Refined force estimates are obtained by adopting and modifying a nonparametric Bayesian modeling technique, the Hierarchical Dirichlet Process Switching Linear Dynamical System (HDP-SLDS), for SPT applications. The HDP-SLDS method shows promise in systematically identifying dynamical regime changes induced by unobserved state changes when the number of underlying states is unknown in advance (a common problem in SPT applications). We expand on the relevance of the HDP-SLDS approach, review the relevant background of Hierarchical Dirichlet Processes, show how to map discrete time HDP-SLDS models to classic SPT models, and discuss limitations of the approach. In addition, we demonstrate new computational techniques for tuning hyperparameters and for checking the statistical consistency of model assumptions directly against individual experimental trajectories; the techniques circumvent the need for "ground-truth" and subjective information.Comment: 25 pages, 6 figures. Differs only typographically from PLoS One publication available freely as an open-access article at http://journals.plos.org/plosone/article?id=10.1371/journal.pone.013763

Geometric constraint subsets and subgraphs in the analysis of assemblies and mechanisms

Geometric Reasoning ability is central to many applications in CAD/CAM/CAPP environments. An increasing demand exists for Geometric Reasoning systems which evaluate the feasibility of virtual scenes specified by geometric relations. Thus, the Geometric Constraint Satisfaction or Scene Feasibility (GCS/SF) problem consists of a basic scenario containing geometric entities, whose context is used to propose constraining relations among still undefined entities. If the constraint specification is consistent, the answer of the problem is one of finitely or infinitely many solution scenarios satisfying the prescribed constraints. Otherwise, a diagnostic of inconsistency is expected. The three main approaches used for this problem are numerical, procedural or operational and mathematical. Numerical and procedural approaches answer only part of the problem, and are not complete in the sense that a failure to provide an answer does not preclude the existence of one. The mathematical approach previously presented by the authors describes the problem using a set of polynomial equations. The common roots to this set of polynomials characterizes the solution space for such a problem. That work presents the use of Groebner basis techniques for verifying the consistency of the constraints. It also integrates subgroups of the Special Euclidean Group of Displacements SE(3) in the problem formulation to exploit the structure implied by geometric relations. Although theoretically sound, these techniques require large amounts of computing resources. This work proposes Divide-and-Conquer techniques applied to local GCS/SF subproblems to identify strongly constrained clusters of geometric entities. The identification and preprocessing of these clusters generally reduces the effort required in solving the overall problem. Cluster identification can be related to identifying short cycles in the Spatial Constraint graph for the GCS/SF problem. Their preprocessing uses the aforementioned Algebraic Geometry and Group theoretical techniques on the local GCS/SF problems that correspond to these cycles. Besides improving the efficiency of the solution approach, the Divide-and-Conquer techniques capture the physical essence of the problem. This is illustrated by applying the discussed techniques to the analysis of the degrees of freedom of mechanisms.MSC: 68U07La habilidad del Razonamiento Geométrico es central a muchas aplicaciones de CAD/CAM/CAPP (Computer Aided Design, Manufacturing and Process Planning). Existe una demanda creciente de sistemas de Razonamiento Geométrico que evalúen la factibilidad de escenas virtuales, especificados por relaciones geométricas. Por lo tanto, el problema de Satisfacción de Restricciones Geométricas o de Factibilidad de Escena (GCS/SF) consta de un escenario básico conteniendo entidades geométricas, cuyo contexto es usado para proponer relaciones de restricción entre entidades aún indefinidas. Si la especificación de las restricciones es consistente, la respuesta al problema es uno del finito o infinito número de escenarios solución que satisfacen las restricciones propuestas. De otra forma, un diagnóstico de inconsistencia es esperado. Las tres principales estrategias usadas para este problema son: numérica, procedimental y matemática. Las soluciones numérica y procedimental resuelven solo parte del problema, y no son completas en el sentido de que una ausencia de respuesta no significa la ausencia de ella. La aproximación matemática previamente presentada por los autores describe el problema usando una serie de ecuaciones polinómicas. Las raíces comunes a este conjunto de polinomios caracterizan el espacio solución para el problema. Ese trabajo presenta el uso de técnicas con Bases de Groebner para verificar la consistencia de las restricciones. Ella también integra los subgrupos del grupo especial Euclídeo de desplazamientos SE(3) en la formulación del problema para explotar la estructura implicada por las relaciones geométricas. Aunque teóricamente sólidas, estas técnicas requieren grandes cantidades de recursos computacionales. Este trabajo propone técnicas de Dividir y Conquistar aplicadas a subproblemas GCS/SF locales para identificar conjuntos de entidades geométricas fuertemente restringidas entre sí. La identificación y pre-procesamiento de dichos conjuntos locales, generalmente reduce el esfuerzo requerido para resolver el problema completo. La identificación de dichos sub-problemas locales está relacionada con la identificación de ciclos cortos en el grafo de Restricciones Geométricas del problema GCS/SF. Su preprocesamiento usa las ya mencionadas técnicas de Geometría Algebraica y Grupos en los problemas locales que corresponden a dichos ciclos. Además de mejorar la eficiencia de la solución, las técnicas de Dividir y Conquistar capturan la esencia física del problema. Esto es ilustrado por medio de su aplicación al análisis de grados de libertad de mecanismos.MSC: 68U0

Environmental Protection Bureau leadership at the provincial level in China: Examining diverging career backgrounds and appointment patterns

This paper analyzes the career backgrounds of local government officials in provincial Environmental Protection Bureaus (EPBs) in China and explains appointment processes of Chinese EPB bureaucrats. Using biographical information of provincial EPB heads and drawing on extensive fieldwork conducted in 2010 in Shanxi Province and Inner Mongolia, this paper finds that only one-fourth of current EPB heads were promoted through the bureau ranks within the EPB, while the remaining three-fourths were appointed from positions outside the environment field. Further, nearly all EPB heads' professional backgrounds and associated networks can be clearly categorized as environmental, business, provincial government, or local government oriented. The paper delineates these four types of Chinese EPB leaders and explains why an awareness of the different professional orientations is critical to understanding environmental protection in China. These findings have implications for inferring the unique characteristics of a province's EPB leadership, the implementation capacities of provincial EPBs, and the appointment preferences of provincial leaders. --agency,environmental protection,policy implementation,networks,China

An Ontology-based approach to integrating life cycle analysis and computer aided design

Ponencia presentada en el XII Congreso Internacional de Ingeniería de Proyectos celebrado en Zaragoza en el año 2008One of the principal problems faced by engineering design today is the exchange of product information across different applications and environments. Ontological engineering systems, an evolution of KBE (Knowledge-Based Engineering) systems, seek to facilitate this integration while incorporating additional design information. An ontology, in the engineering domain, can be defined as an explicit specification of a shared conceptualization. This paper proposes the integration of an ontology with a Computer Aided Design (CAD) program, while also accessing a database of information on environmental impact. The proposed ontology is based on the AsD (Assembly Design) formalism, which describes spatial relationships and features of CAD models. The use of OWL (Web Ontology Language) and SWRL (Semantic Web Rule Language) ensures machine interpretability and exchange across different environments. Ultimately, the ontology will be used to represent a CAD model and related information (such as joining methods, materials, tolerances) in formal terms. Concurrently, a database of information on environmental impact of the materials, processes and transport involved will be accessed to evaluate the model on an environmental level. As a practical illustration, the evaluation of an underwater camera is used as an example

Inner Space Preserving Generative Pose Machine

Image-based generative methods, such as generative adversarial networks (GANs) have already been able to generate realistic images with much context control, specially when they are conditioned. However, most successful frameworks share a common procedure which performs an image-to-image translation with pose of figures in the image untouched. When the objective is reposing a figure in an image while preserving the rest of the image, the state-of-the-art mainly assumes a single rigid body with simple background and limited pose shift, which can hardly be extended to the images under normal settings. In this paper, we introduce an image "inner space" preserving model that assigns an interpretable low-dimensional pose descriptor (LDPD) to an articulated figure in the image. Figure reposing is then generated by passing the LDPD and the original image through multi-stage augmented hourglass networks in a conditional GAN structure, called inner space preserving generative pose machine (ISP-GPM). We evaluated ISP-GPM on reposing human figures, which are highly articulated with versatile variations. Test of a state-of-the-art pose estimator on our reposed dataset gave an accuracy over 80% on PCK0.5 metric. The results also elucidated that our ISP-GPM is able to preserve the background with high accuracy while reasonably recovering the area blocked by the figure to be reposed.Comment: http://www.northeastern.edu/ostadabbas/2018/07/23/inner-space-preserving-generative-pose-machine