51,604 research outputs found

    A Fast Modal Space Transform for Robust Nonrigid Shape Retrieval

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    Nonrigid or deformable 3D objects are common in many application domains. Retrieval of such objects in large databases based on shape similarity is still a challenging problem. In this paper, we take advantages of functional operators as characterizations of shape deformation, and further propose a framework to design novel shape signatures for encoding nonrigid geometries. Our approach constructs a context-aware integral kernel operator on a manifold, then applies modal analysis to map this operator into a low-frequency functional representation, called fast functional transform, and finally computes its spectrum as the shape signature. In a nutshell, our method is fast, isometry-invariant, discriminative, smooth and numerically stable with respect to multiple types of perturbations. Experimental results demonstrate that our new shape signature for nonrigid objects can outperform all methods participating in the nonrigid track of the SHREC’11 contest. It is also the second best performing method in the real human model track of SHREC’14.postprin

    A semantic web approach for built heritage representation

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    In a built heritage process, meant as a structured system of activities aimed at the investigation, preservation, and management of architectural heritage, any task accomplished by the several actors involved in it is deeply influenced by the way the knowledge is represented and shared. In the current heritage practice, knowledge representation and management have shown several limitations due to the difficulty of dealing with large amount of extremely heterogeneous data. On this basis, this research aims at extending semantic web approaches and technologies to architectural heritage knowledge management in order to provide an integrated and multidisciplinary representation of the artifact and of the knowledge necessary to support any decision or any intervention and management activity. To this purpose, an ontology-based system, representing the knowledge related to the artifact and its contexts, has been developed through the formalization of domain-specific entities and relationships between them

    Kernel arquitecture for CAD/CAM in shipbuilding enviroments

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    The capabilities of complex software products such as CAD/CAM systems are strongly supported by basic information technologies related with data management, visualization, communication, geometry modeling and others related with the development process. These basic information technologies are involved in a continuous evolution process, but over recent years this evolution has been dramatic. The main reason for this has been that new hardware capabilities (including graphic cards) are available at very low cost, but also a contributing factor has been the evolution of the prices of basic software. To take advantage of these new features, the existing CAD/CAM systems must undergo a complete and drastic redesign. This process is complicated but strategic for the future evolution of a system. There are several examples in the market of how a bad decision has lead to a cul-de-sac (both technically and commercially). This paper describes what the authors consider are the basic architectural components of a kernel for a CAD/CAM system oriented to shipbuilding. The proposed solution is a combination of in-house developed frameworks together with commercial products that are accepted as standard components. The proportion of in-house frameworks within this combination of products is a key factor, especially when considering CAD/CAM systems oriented to shipbuilding. General-purpose CAD/CAM systems are mainly oriented to the mechanical CAD market. For this reason several basic products exist devoted to geometry modelling in this context. But these basic products are not well suited to deal with the very specific geometry modelling requirements of a CAD/CAM system oriented to shipbuilding. The complexity of the ship model, the different model requirements through its short and changing life cycle and the many different disciplines involved in the process are reasons for this inadequacy. Apart from these basic frameworks, specific shipbuilding frameworks are also required. This second layer is built over the basic technology components mentioned above. This paper describes in detail the technological frameworks which have been used to develop the latest FORAN version.Postprint (published version

    Furniture models learned from the WWW: using web catalogs to locate and categorize unknown furniture pieces in 3D laser scans

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    In this article, we investigate how autonomous robots can exploit the high quality information already available from the WWW concerning 3-D models of office furniture. Apart from the hobbyist effort in Google 3-D Warehouse, many companies providing office furnishings already have the models for considerable portions of the objects found in our workplaces and homes. In particular, we present an approach that allows a robot to learn generic models of typical office furniture using examples found in the Web. These generic models are then used by the robot to locate and categorize unknown furniture in real indoor environments

    Action Recognition in Videos: from Motion Capture Labs to the Web

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    This paper presents a survey of human action recognition approaches based on visual data recorded from a single video camera. We propose an organizing framework which puts in evidence the evolution of the area, with techniques moving from heavily constrained motion capture scenarios towards more challenging, realistic, "in the wild" videos. The proposed organization is based on the representation used as input for the recognition task, emphasizing the hypothesis assumed and thus, the constraints imposed on the type of video that each technique is able to address. Expliciting the hypothesis and constraints makes the framework particularly useful to select a method, given an application. Another advantage of the proposed organization is that it allows categorizing newest approaches seamlessly with traditional ones, while providing an insightful perspective of the evolution of the action recognition task up to now. That perspective is the basis for the discussion in the end of the paper, where we also present the main open issues in the area.Comment: Preprint submitted to CVIU, survey paper, 46 pages, 2 figures, 4 table

    A deep representation for depth images from synthetic data

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    Convolutional Neural Networks (CNNs) trained on large scale RGB databases have become the secret sauce in the majority of recent approaches for object categorization from RGB-D data. Thanks to colorization techniques, these methods exploit the filters learned from 2D images to extract meaningful representations in 2.5D. Still, the perceptual signature of these two kind of images is very different, with the first usually strongly characterized by textures, and the second mostly by silhouettes of objects. Ideally, one would like to have two CNNs, one for RGB and one for depth, each trained on a suitable data collection, able to capture the perceptual properties of each channel for the task at hand. This has not been possible so far, due to the lack of a suitable depth database. This paper addresses this issue, proposing to opt for synthetically generated images rather than collecting by hand a 2.5D large scale database. While being clearly a proxy for real data, synthetic images allow to trade quality for quantity, making it possible to generate a virtually infinite amount of data. We show that the filters learned from such data collection, using the very same architecture typically used on visual data, learns very different filters, resulting in depth features (a) able to better characterize the different facets of depth images, and (b) complementary with respect to those derived from CNNs pre-trained on 2D datasets. Experiments on two publicly available databases show the power of our approach

    Utilizing a 3D game engine to develop a virtual design review system

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    A design review process is where information is exchanged between the designers and design reviewers to resolve any potential design related issues, and to ensure that the interests and goals of the owner are met. The effective execution of design review will minimize potential errors or conflicts, reduce the time for review, shorten the project life-cycle, allow for earlier occupancy, and ultimately translate into significant total project savings to the owner. However, the current methods of design review are still heavily relying on 2D paper-based format, sequential and lack central and integrated information base for efficient exchange and flow of information. There is thus a need for the use of a new medium that allow for 3D visualization of designs, collaboration among designers and design reviewers, and early and easy access to design review information. This paper documents the innovative utilization of a 3D game engine, the Torque Game Engine as the underlying tool and enabling technology for a design review system, the Virtual Design Review System for architectural designs. Two major elements are incorporated; 1) a 3D game engine as the driving tool for the development and implementation of design review processes, and 2) a virtual environment as the medium for design review, where visualization of design and design review information is based on sound principles of GUI design. The development of the VDRS involves two major phases; firstly, the creation of the assets and the assembly of the virtual environment, and secondly, the modification of existing functions or introducing new functionality through programming of the 3D game engine in order to support design review in a virtual environment. The features that are included in the VDRS are support for database, real-time collaboration across network, viewing and navigation modes, 3D object manipulation, parametric input, GUI, and organization for 3D objects
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