Showing papers in "Computers & Graphics in 2016"

TL;DR: An automatic approach for the reconstruction of parametric 3D building models from indoor point clouds that goes beyond mere surface reconstruction of previous reconstruction methods and enables intuitive editing on level of building elements, e.g. moving whole walls.

TL;DR: The experimental results show that the efficiency of Delaunay triangulation by the adaptive Hilbert curve insertion algorithm can be improved significantly for both uniformly and non-uniformly distributed point cloud data, compared with CGAL, regular grid insertion and multi-grid insertion algorithms.

TL;DR: An automatic reconstruction pipeline for large scale urban scenes from aerial images captured by a camera mounted on an unmanned aerial vehicle and an effective contour refinement method based on pivot point detection are presented.

TL;DR: SlidAR is presented, a 3D positioning for Simultaneous Localization And Mapping (SLAM) based HAR systems that utilizes 3D ray-casting and epipolar geometry for virtual object positioning and does not require a perfect 3D reconstruction of the environment nor any virtual depth cues.

TL;DR: This work combines the detection of individual objects and object groups within the same framework, enabling contextual analysis without knowing objects, and demonstrates that the unified contextual analysis framework achieves robust object detection and recognition over cluttered subscenes.

TL;DR: A data-partitioning error-controlled strategy for solving the nearest neighbor search (NNS) problem using spatial sorting as the basic building block is presented, providing significant performance and precision gains over previous works.

TL;DR: This paper presents an interactive system for transforming images into an oil paint look that employs non-linear filtering based on the smoothed structure adapted to the main feature contours of the quantized image to synthesize a paint texture in real-time.

TL;DR: An interactive visualization system to explore the dynamics of public bike-sharing systems by profiling its historical dataset is introduced, coordinating a pixel-oriented timeline with a map, and introducing a scheme of partial reordering of time series to understand the commuting dynamics.

TL;DR: A heuristic criterion for optimal knot positions in the fitting problem is formulated as an optimization problem according to the geometric feature distribution of the input data, and the coordinate descent algorithm is used for the optimal knot computation.

TL;DR: An online parameter learning algorithm for data-driven crowd simulation and crowd content generation based on incrementally learning pedestrian motion models and behaviors from crowd videos and refined using an optimization technique to estimate the agents' simulation parameters.

TL;DR: The proposed Poisson distribution based method does not need any prior surface reconstruction and is not largely affected by noisy points, neighborhood scales or sampling quality, and goes beyond user-setting feature measure thresholds of previous feature extraction methods.

TL;DR: It is shown that the proposed method produces unfoldable segmentation that resembles carefully designed paper craft, and the key idea that enables this capability is an algorithm that learns from failed unfoldings.

TL;DR: A novel construction of subspaces for real-time deformation-based modeling and shape interpolation by automatically sample the deformation manifold and constructing the subspace that optimally approximates the manifold of deformations relevant for a specific modeling or interpolation problem.

TL;DR: ShipShape is presented-a general beautification assistant that allows users to maintain the simplicity and speed of freehand sketching while still taking into account implicit geometric relations to automatically rectify the output image.

TL;DR: A novel graph construction method which connects the joints that are deemed important for a given motion that is robust under several variations, and demonstrates superior performance in comparison to three state-of-the-art methods.

TL;DR: The proposed method relies on a clustering mechanism to group attributes in order to mitigate visual clutter, allowing the analysis of how particular groups of attributes impact on the radial layout, thus assisting users in the understanding of data.

TL;DR: This paper provides the first and comprehensive reference source of shape context based mesh saliency for researchers from a wide range of domains, including but not limited to computer graphics and vision.

TL;DR: The 2D Shape Structure database is presented, a public, user-generated dataset of 2D shape decompositions into a hierarchy of shape parts with geometric relationships retained, providing the shape community with a ground truth of human perception of holistic shape structure.

TL;DR: This study collected 2276 papers from three scientific databases using an open-source crawler, from which 360 were selected to be classified according to four properties: tracking type, degree of freedom, tracking platform and research type to provide trends and classification regarding the recent publications in the area of tracking for mobile devices.

TL;DR: In this extended work, the effectiveness of Penny Pincher in a stressful setting using a video game prototype that makes heavy use of gestures is evaluated, so that rushed and malformed gesture articulation is more likely.

TL;DR: The results of a systematic mapping study of existing work are reported, and a taxonomy categorizing digital ink annotation research is presented, showing the successful techniques and the remaining challenges since there has not yet been a comprehensive review of digital ink annotations research.

TL;DR: This work considers the problem of finding a unit vector field over a domain that balances two competing objectives, smoothness and conformity to the shape of the domain, and analyzes the relation between extrinsic smoothness, intrinsic smooths, and shape conformity in a continuous and general setting.

TL;DR: It is found that the expressive capability of hand articulation can be effectively harnessed for controllable shaping by organizing the deformation process in broad classes of intended operations such as pulling, pushing, and fairing.

TL;DR: A novel method for the modeling and optimization of the material distribution inside 3D shapes, such that their 3D printed replicas satisfy prescribed constraints regarding mass properties, and an extension of ray-representation to shape interior modeling that covers the optimal interior regarding static and rotational stability criteria.

TL;DR: A new tool for vector field uncertainty analysis based on the Helmholtz-Hodge decomposition, which uses the curl-free and divergence-free orthogonal components for uncertainty investigation and uses a rank correlation coefficient to quantify the contribution of each component to the total uncertainty.

TL;DR: An interactive and light-weight system that allows to paint large-scale murals and performs at haptic rates, which allows the user - informed by a visualization of the image residual - to guide the system interactively to recover low frequency features.

TL;DR: While prior work in a laboratory setting suggests that long pauses are indicative of low competence, this work shows that the frequency of long pauses during exams correlates positively with competence, and a novel approach for measuring the correctness of exam solutions from an analysis of lexical features of handwritten equations.

TL;DR: PinMesh is a very fast algorithm with implementation to preprocess a polyhedral mesh, also known as a multi-material mesh, in order to perform 3D point location queries and is intended to be a subroutine in more complex algorithms.

TL;DR: This work presents a novel method for high-quality blue-noise sampling on mesh surfaces with prescribed cell-sizes for the underlying tessellation (capacity constraint) and extends this framework to handle multi-capacity constraints.