246 research outputs found

    Novel 3D compression methods for geometry, connectivity and texture

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    A large number of applications in medical visualization, games, engineering design, entertainment, heritage, e-commerce and so on require the transmission of 3D models over the Internet or over local networks. 3D data compression is an important requirement for fast data storage, access and transmission within bandwidth limitations. The Wavefront OBJ (object) file format is commonly used to share models due to its clear simple design. Normally each OBJ file contains a large amount of data (e.g. vertices and triangulated faces, normals, texture coordinates and other parameters) describing the mesh surface. In this paper we introduce a new method to compress geometry, connectivity and texture coordinates by a novel Geometry Minimization Algorithm (GM-Algorithm) in connection with arithmetic coding. First, each vertex (x, y, z) coordinates are encoded to a single value by the GM-Algorithm. Second, triangle faces are encoded by computing the differences between two adjacent vertex locations, which are compressed by arithmetic coding together with texture coordinates. We demonstrate the method on large data sets achieving compression ratios between 87%—99% without reduction in the number of reconstructed vertices and triangle faces. The decompression step is based on a Parallel Fast Matching Search Algorithm (Parallel-FMS) to recover the structure of the 3D mesh. A comparative analysis of compression ratios is provided with a number of commonly used 3D file formats such as VRML, OpenCTM and STL highlighting the performance and effectiveness of the proposed method

    Optimal Estimation of Matching Constraints

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    International audienceWe describe work in progress on a numerical library for estimating multi-image matching constraints, or more precisely the multi-camera geometry underlying them. The library will cover several variants of homographic, epipolar, and trifocal constraints, using various different feature types. It is designed to be modular and open-ended, so that (i) new feature types or error models, (ii) new constraint types or parametrizations, and (iii) new numerical resolution methods, are relatively easy to add. The ultimate goal is to provide practical code for stable, reliable, statistically optimal estimation of matching geometry under a choice of robust error models, taking full account of any nonlinear constraints involved. More immediately, the library will be used to study the relative performance of the various competing problem parametrizations, error models and numerical methods. The paper focuses on the overall design, parametrization and numerical optimization issues. The methods described extend to many other geometric estimation problems in vision, e.g. curve and surface fitting

    Application of the Fisher-Rao metric to ellipse detection

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    The parameter space for the ellipses in a two dimensional image is a five dimensional manifold, where each point of the manifold corresponds to an ellipse in the image. The parameter space becomes a Riemannian manifold under a Fisher-Rao metric, which is derived from a Gaussian model for the blurring of ellipses in the image. Two points in the parameter space are close together under the Fisher-Rao metric if the corresponding ellipses are close together in the image. The Fisher-Rao metric is accurately approximated by a simpler metric under the assumption that the blurring is small compared with the sizes of the ellipses under consideration. It is shown that the parameter space for the ellipses in the image has a finite volume under the approximation to the Fisher-Rao metric. As a consequence the parameter space can be replaced, for the purpose of ellipse detection, by a finite set of points sampled from it. An efficient algorithm for sampling the parameter space is described. The algorithm uses the fact that the approximating metric is flat, and therefore locally Euclidean, on each three dimensional family of ellipses with a fixed orientation and a fixed eccentricity. Once the sample points have been obtained, ellipses are detected in a given image by checking each sample point in turn to see if the corresponding ellipse is supported by the nearby image pixel values. The resulting algorithm for ellipse detection is implemented. A multiresolution version of the algorithm is also implemented. The experimental results suggest that ellipses can be reliably detected in a given low resolution image and that the number of false detections can be reduced using the multiresolution algorithm

    Monte Carlo simulations of fluid vesicles with in plane orientational ordering

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    We present a method for simulating fluid vesicles with in-plane orientational ordering. The method involves computation of local curvature tensor and parallel transport of the orientational field on a randomly triangulated surface. It is shown that the model reproduces the known equilibrium conformation of fluid membranes and work well for a large range of bending rigidities. Introduction of nematic ordering leads to stiffening of the membrane. Nematic ordering can also result in anisotropic rigidity on the surface leading to formation of membrane tubes.Comment: 11 Pages, 12 Figures, To appear in Phys. Rev.

    Local implicit modeling of blood vessels for interactive simulation

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    International audienceIn the context of computer-based simulation, contact management requires an accurate, smooth, but still efficient surface model for the blood vessels. A new implicit model is proposed, consisting of a tree of local implicit surfaces generated by skeletons ({\em blobby models}). The surface is reconstructed from data points by minimizing an energy, alternating with an original blob selection and subdivision scheme. The reconstructed models are very efficient for simulation and were shown to provide a sub-voxel approximation of the vessel surface on 5 patients

    From Multiview Image Curves to 3D Drawings

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    Reconstructing 3D scenes from multiple views has made impressive strides in recent years, chiefly by correlating isolated feature points, intensity patterns, or curvilinear structures. In the general setting - without controlled acquisition, abundant texture, curves and surfaces following specific models or limiting scene complexity - most methods produce unorganized point clouds, meshes, or voxel representations, with some exceptions producing unorganized clouds of 3D curve fragments. Ideally, many applications require structured representations of curves, surfaces and their spatial relationships. This paper presents a step in this direction by formulating an approach that combines 2D image curves into a collection of 3D curves, with topological connectivity between them represented as a 3D graph. This results in a 3D drawing, which is complementary to surface representations in the same sense as a 3D scaffold complements a tent taut over it. We evaluate our results against truth on synthetic and real datasets.Comment: Expanded ECCV 2016 version with tweaked figures and including an overview of the supplementary material available at multiview-3d-drawing.sourceforge.ne

    A model for adapting 3D graphics based on scalable coding, real-time simplification and remote rendering

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    Most current multiplayer 3D games can only be played on dedicated platforms, requiring specifically designed content and communication over a predefined network. To overcome these limitations, the OLGA (On-Line GAming) consortium has devised a framework to develop distributive, multiplayer 3D games. Scalability at the level of content, platforms and networks is exploited to achieve the best trade-offs between complexity and quality

    Connectivity forests for homological analysis of digital volumes

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    In this paper, we provide a graph-based representation of the homology (information related to the different “holes” the object has) of a binary digital volume. We analyze the digital volume AT-model representation [8] from this point of view and the cellular version of the AT-model [5] is precisely described here as three forests (connectivity forests), from which, for instance, we can straightforwardly determine representative curves of “tunnels” and “holes”, classify cycles in the complex, computing higher (co)homology operations,... Depending of the order in which we gradually construct these trees, tools so important in Computer Vision and Digital Image Processing as Reeb graphs and topological skeletons appear as results of pruning these graphs

    Non-Iterative, Feature-Preserving Mesh Smoothing

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    With the increasing use of geometry scanners to create 3D models, there is a rising need for fast and robust mesh smoothing to remove inevitable noise in the measurements. While most previous work has favored diffusion-based iterative techniques for feature-preserving smoothing, we propose a radically different approach, based on robust statistics and local first-order predictors of the surface. The robustness of our local estimates allows us to derive a non-iterative feature-preserving filtering technique applicable to arbitrary "triangle soups". We demonstrate its simplicity of implementation and its efficiency, which make it an excellent solution for smoothing large, noisy, and non-manifold meshes.Singapore-MIT Alliance (SMA

    Steganalysis of 3D objects using statistics of local feature sets

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    3D steganalysis aims to identify subtle invisible changes produced in graphical objects through digital watermarking or steganography. Sets of statistical representations of 3D features, extracted from both cover and stego 3D mesh objects, are used as inputs into machine learning classifiers in order to decide whether any information was hidden in the given graphical object. The features proposed in this paper include those representing the local object curvature, vertex normals, the local geometry representation in the spherical coordinate system. The effectiveness of these features is tested in various combinations with other features used for 3D steganalysis. The relevance of each feature for 3D steganalysis is assessed using the Pearson correlation coefficient. Six different 3D watermarking and steganographic methods are used for creating the stego-objects used in the evaluation study
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