Strategic Port Graph Rewriting: An Interactive Modelling and Analysis Framework

We present strategic portgraph rewriting as a basis for the implementation of visual modelling and analysis tools. The goal is to facilitate the specification, analysis and simulation of complex systems, using port graphs. A system is represented by an initial graph and a collection of graph rewriting rules, together with a user-defined strategy to control the application of rules. The strategy language includes constructs to deal with graph traversal and management of rewriting positions in the graph. We give a small-step operational semantics for the language, and describe its implementation in the graph transformation and visualisation tool PORGY.Comment: In Proceedings GRAPHITE 2014, arXiv:1407.767

Ten virtues of structured graphs

This paper extends the invited talk by the first author about the virtues of structured graphs. The motivation behind the talk and this paper relies on our experience on the development of ADR, a formal approach for the design of styleconformant, reconfigurable software systems. ADR is based on hierarchical graphs with interfaces and it has been conceived in the attempt of reconciling software architectures and process calculi by means of graphical methods. We have tried to write an ADR agnostic paper where we raise some drawbacks of flat, unstructured graphs for the design and analysis of software systems and we argue that hierarchical, structured graphs can alleviate such drawbacks

Graph Data Conversion and Tree Visualization

The first part of the paper is converting graph data format from GXL to GraphML. GXL and GraphML are both XML-based languages for representing graph data. The HP page segmentation tool produces output graph data in GXL format, and the Visual Environment for Graph Grammar Induction and Engineering (VEGGIE) tool takes input graph data in GraphML format. To make these two tools interoperable, the Graph Data converter changes a GXL graph structure data input into a GraphML graph structure output. XSLT is used by this tool for conversion; XSLT is a simple, functional language that is often used to convert an input XML document into an output XML document. The second part of the paper focuses on tree visualization to generate additional views in VEGGIE for a given graph. Present VEGGIE tree visualization is limited to JTree View which makes it hard to analyze a complex user interface. For in-depth analysis of user interfaces, we need more user-friendly and interactive tree views. Moreover, for further analysis, it is useful if the generated views can be saved. Prefuse libraries are used to enhance the VEGGIE views. Prefuse is a Java-based visualization toolkit: it provides rich, interactive, and user-friendly visualizations. VEGGIE is enhanced with GraphView, TreeView, and Simplified Tree view. HTML is also generated to view the tree structure in HTML browsers

ShapeCoder: Discovering Abstractions for Visual Programs from Unstructured Primitives

We introduce ShapeCoder, the first system capable of taking a dataset of shapes, represented with unstructured primitives, and jointly discovering (i) useful abstraction functions and (ii) programs that use these abstractions to explain the input shapes. The discovered abstractions capture common patterns (both structural and parametric) across a dataset, so that programs rewritten with these abstractions are more compact, and suppress spurious degrees of freedom. ShapeCoder improves upon previous abstraction discovery methods, finding better abstractions, for more complex inputs, under less stringent input assumptions. This is principally made possible by two methodological advancements: (a) a shape-to-program recognition network that learns to solve sub-problems and (b) the use of e-graphs, augmented with a conditional rewrite scheme, to determine when abstractions with complex parametric expressions can be applied, in a tractable manner. We evaluate ShapeCoder on multiple datasets of 3D shapes, where primitive decompositions are either parsed from manual annotations or produced by an unsupervised cuboid abstraction method. In all domains, ShapeCoder discovers a library of abstractions that captures high-level relationships, removes extraneous degrees of freedom, and achieves better dataset compression compared with alternative approaches. Finally, we investigate how programs rewritten to use discovered abstractions prove useful for downstream tasks

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

Spatially Aware Computing for Natural Interaction

Spatial information refers to the location of an object in a physical or digital world. Besides, it also includes the relative position of an object related to other objects around it. In this dissertation, three systems are designed and developed. All of them apply spatial information in different fields. The ultimate goal is to increase the user friendliness and efficiency in those applications by utilizing spatial information. The first system is a novel Web page data extraction application, which takes advantage of 2D spatial information to discover structured records from a Web page. The extracted information is useful to re-organize the layout of a Web page to fit mobile browsing. The second application utilizes the 3D spatial information of a mobile device within a large paper-based workspace to implement interactive paper that combines the merits of paper documents and mobile devices. This application can overlay digital information on top of a paper document based on the location of a mobile device within a workspace. The third application further integrates 3D space information with sound detection to realize an automatic camera management system. This application automatically controls multiple cameras in a conference room, and creates an engaging video by intelligently switching camera shots among meeting participants based on their activities. Evaluations have been made on all three applications, and the results are promising. In summary, this dissertation comprehensively explores the usage of spatial information in various applications to improve the usability