EG 2018 - STARs (CGF 37-2)

Permanent URI for this collection

https://diglib.eg.org/handle/10.2312/2632163

Browse

Browsing EG 2018 - STARs (CGF 37-2) by Subject "Shape analysis"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Functionality Representations and Applications for Shape Analysis
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Hu, Ruizhen; Savva, Manolis; Kaick, Oliver van; Hildebrandt, Klaus and Theobalt, Christian
    A central goal of computer graphics is to provide tools for designing and simulating real or imagined artifacts. An understanding of functionality is important in enabling such modeling tools. Given that the majority of man-made artifacts are designed to serve a certain function, the functionality of objects is often reflected by their geometry, the way that they are organized in an environment, and their interaction with other objects or agents. Thus, in recent years, a variety of methods in shape analysis have been developed to extract functional information about objects and scenes from these different types of cues. In this report, we discuss recent developments that incorporate functionality aspects into the analysis of 3D shapes and scenes. We provide a summary of the state-of-the-art in this area, including a discussion of key ideas and an organized review of the relevant literature. More specifically, the report is structured around a general definition of functionality from which we derive criteria for classifying the body of prior work. This definition also facilitates a comparative view of methods for functionality analysis. We focus on studying the inference of functionality from a geometric perspective, and pose functionality analysis as a process involving both the geometry and interactions of a functional entity. In addition, we discuss a variety of applications that benefit from an analysis of functionality, and conclude the report with a discussion of current challenges and potential future works.
  • Thumbnail Image
    Item
    A Survey on Data-driven Dictionary-based Methods for 3D Modeling
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Lescoat, Thibault; Ovsjanikov, Maks; Memari, Pooran; Thiery, Jean-Marc; Boubekeur, Tamy; Hildebrandt, Klaus and Theobalt, Christian
    Dictionaries are very useful objects for data analysis, as they enable a compact representation of large sets of objects through the combination of atoms. Dictionary-based techniques have also particularly benefited from the recent advances in machine learning, which has allowed for data-driven algorithms to take advantage of the redundancy in the input dataset and discover relations between objects without human supervision or hard-coded rules. Despite the success of dictionary-based techniques on a wide range of tasks in geometric modeling and geometry processing, the literature is missing a principled state-of-the-art of the current knowledge in this field. To fill this gap, we provide in this survey an overview of data-driven dictionary-based methods in geometric modeling. We structure our discussion by application domain: surface reconstruction, compression, and synthesis. Contrary to previous surveys, we place special emphasis on dictionary-based methods suitable for 3D data synthesis, with applications in geometric modeling and design. Our ultimate goal is to enlight the fact that these techniques can be used to combine the data-driven paradigm with design intent to synthesize new plausible objects with minimal human intervention. This is the main motivation to restrict the scope of the present survey to techniques handling point clouds and meshes, making use of dictionaries whose definition depends on the input data, and enabling shape reconstruction or synthesis through the combination of atoms.