546,550 research outputs found

    Linear Shape Deformation Models with Local Support Using Graph-based Structured Matrix Factorisation

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    Representing 3D shape deformations by linear models in high-dimensional space has many applications in computer vision and medical imaging, such as shape-based interpolation or segmentation. Commonly, using Principal Components Analysis a low-dimensional (affine) subspace of the high-dimensional shape space is determined. However, the resulting factors (the most dominant eigenvectors of the covariance matrix) have global support, i.e. changing the coefficient of a single factor deforms the entire shape. In this paper, a method to obtain deformation factors with local support is presented. The benefits of such models include better flexibility and interpretability as well as the possibility of interactively deforming shapes locally. For that, based on a well-grounded theoretical motivation, we formulate a matrix factorisation problem employing sparsity and graph-based regularisation terms. We demonstrate that for brain shapes our method outperforms the state of the art in local support models with respect to generalisation ability and sparse shape reconstruction, whereas for human body shapes our method gives more realistic deformations.Comment: Please cite CVPR 2016 versio

    Deformable Shape Completion with Graph Convolutional Autoencoders

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    The availability of affordable and portable depth sensors has made scanning objects and people simpler than ever. However, dealing with occlusions and missing parts is still a significant challenge. The problem of reconstructing a (possibly non-rigidly moving) 3D object from a single or multiple partial scans has received increasing attention in recent years. In this work, we propose a novel learning-based method for the completion of partial shapes. Unlike the majority of existing approaches, our method focuses on objects that can undergo non-rigid deformations. The core of our method is a variational autoencoder with graph convolutional operations that learns a latent space for complete realistic shapes. At inference, we optimize to find the representation in this latent space that best fits the generated shape to the known partial input. The completed shape exhibits a realistic appearance on the unknown part. We show promising results towards the completion of synthetic and real scans of human body and face meshes exhibiting different styles of articulation and partiality.Comment: CVPR 201

    A robust nonlinear scale space change detection approach for SAR images

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    In this paper, we propose a change detection approach based on nonlinear scale space analysis of change images for robust detection of various changes incurred by natural phenomena and/or human activities in Synthetic Aperture Radar (SAR) images using Maximally Stable Extremal Regions (MSERs). To achieve this, a variant of the log-ratio image of multitemporal images is calculated which is followed by Feature Preserving Despeckling (FPD) to generate nonlinear scale space images exhibiting different trade-offs in terms of speckle reduction and shape detail preservation. MSERs of each scale space image are found and then combined through a decision level fusion strategy, namely "selective scale fusion" (SSF), where contrast and boundary curvature of each MSER are considered. The performance of the proposed method is evaluated using real multitemporal high resolution TerraSAR-X images and synthetically generated multitemporal images composed of shapes with several orientations, sizes, and backscatter amplitude levels representing a variety of possible signatures of change. One of the main outcomes of this approach is that different objects having different sizes and levels of contrast with their surroundings appear as stable regions at different scale space images thus the fusion of results from scale space images yields a good overall performance

    Creativity Process In The Product Development Of Urban Toys Called The Power Anger

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    Bandung is a gathering place for creative groups that produce creative products. Urban toys are toys that have visual meaning by applying symbols into the shape of characters. Starting from the anxiety of the creator through the process of creativity, the toy products are power angers. The making of this figure starts from visual references which are combined with shapes and colours that correspond to the meaning on the basis of the type of human nature. The process of creativity used is imitative creativity (unconscious), the researcher looks at the creator in the space and time of the process of creating a product until product development. The development of the figure “the power anger” product is a collaboration of ideas with other creators to create different new products. Keywords: Urban Toy, Creativity, Product Development

    Evaluating the Effectiveness of Shielding Material, Vehicle Shape and Astronaut Position for Deep Space Travel

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    Background: As future crewed, deep space missions are being planned, it is important to assess how spacecraft design can be used to minimize radiation exposure. Collectively with shielding material, vehicle shape and astronaut position must be used to protect astronauts from the two primary sources of space radiation: Galactic Cosmic Rays (GCRs) and Solar Particle Events (SPEs). Methods: The On-Line Tool for the Assessment of Radiation in Space (OLTARIS) version 4.1 analysis package is used to evaluate and analyze this detailed radiation field. Developed by the National Aeronautics and Space Administration\u27s (NASA) Langley Research Center, the tool enables engineering and research related space radiation calculations. Each configuration is evaluated in whole body effective dose equivalent (ED). This research evaluates 70 aerospace materials, 2 vehicle shapes and 3 astronaut positions. Results and Conclusions: The material analyses show that for metals, aluminum outperforms and therefore is the most feasible metal for deep space travel. But when evaluating all materials, polyethylene outperforms all feasible aerospace materials. The vehicle shape and astronaut position analyses show that moving a human phantom closer to a wall does significantly decrease the ED. This pattern is not dependent on material nor boundary condition, but the mean shielding thickness a source ray must travel through for the GCR boundary condition. For shielding thicknesses greater than 30 g/cm 2 for polyethylene and 100g/cm 2 for aluminum, the results suggest that having astronauts’ habitats and work areas located further from the center will help protect astronauts longer from deep space radiation.https://scholarscompass.vcu.edu/gradposters/1067/thumbnail.jp
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