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Compact Representation (compact + representation)
Selected AbstractsGeometry-Driven Local Neighbourhood Based Predictors for Dynamic Mesh CompressionCOMPUTER GRAPHICS FORUM, Issue 6 2010Libor Vá Computer Graphics [I.3.7]: Animation Abstract The task of dynamic mesh compression seeks to find a compact representation of a surface animation, while the artifacts introduced by the representation are as small as possible. In this paper, we present two geometric predictors, which are suitable for PCA-based compression schemes. The predictors exploit the knowledge about the geometrical meaning of the data, which allows a more accurate prediction, and thus a more compact representation. We also provide rate/distortion curves showing that our approach outperforms the current PCA-based compression methods by more than 20%. [source] Grammar-based Encoding of FacadesCOMPUTER GRAPHICS FORUM, Issue 4 2010Simon Haegler Abstract In this paper we propose a real-time rendering approach for procedural cities. Our first contribution is a new lightweight grammar representation that compactly encodes facade structures and allows fast per-pixel access. We call this grammar F -shade. Our second contribution is a prototype rendering system that renders an urban model from the compact representation directly on the GPU. Our suggested approach explores an interesting connection from procedural modeling to real-time rendering. Evaluating procedural descriptions at render time uses less memory than the generation of intermediate geometry. This enables us to render large urban models directly from GPU memory. [source] An Exploratory Technique for Coherent Visualization of Time-varying Volume DataCOMPUTER GRAPHICS FORUM, Issue 3 2010A. Tikhonova Abstract The selection of an appropriate global transfer function is essential for visualizing time-varying simulation data. This is especially challenging when the global data range is not known in advance, as is often the case in remote and in-situ visualization settings. Since the data range may vary dramatically as the simulation progresses, volume rendering using local transfer functions may not be coherent for all time steps. We present an exploratory technique that enables coherent classification of time-varying volume data. Unlike previous approaches, which require pre-processing of all time steps, our approach lets the user explore the transfer function space without accessing the original 3D data. This is useful for interactive visualization, and absolutely essential for in-situ visualization, where the entire simulation data range is not known in advance. Our approach generates a compact representation of each time step at rendering time in the form of ray attenuation functions, which are used for subsequent operations on the opacity and color mappings. The presented approach offers interactive exploration of time-varying simulation data that alleviates the cost associated with reloading and caching large data sets. [source] Differential Representations for Mesh ProcessingCOMPUTER GRAPHICS FORUM, Issue 4 2006Olga Sorkine Abstract Surface representation and processing is one of the key topics in computer graphics and geometric modeling, since it greatly affects the range of possible applications. In this paper we will present recent advances in geometry processing that are related to the Laplacian processing framework and differential representations. This framework is based on linear operators defined on polygonal meshes, and furnishes a variety of processing applications, such as shape approximation and compact representation, mesh editing, watermarking and morphing. The core of the framework is the definition of differential coordinates and new bases for efficient mesh geometry representation, based on the mesh Laplacian operator. [source] Visyllable Based Speech AnimationCOMPUTER GRAPHICS FORUM, Issue 3 2003Sumedha Kshirsagar Visemes are visual counterpart of phonemes. Traditionally, the speech animation of 3D synthetic faces involvesextraction of visemes from input speech followed by the application of co-articulation rules to generate realisticanimation. In this paper, we take a novel approach for speech animation , using visyllables, the visual counterpartof syllables. The approach results into a concatenative visyllable based speech animation system. The key contributionof this paper lies in two main areas. Firstly, we define a set of visyllable units for spoken English along withthe associated phonological rules for valid syllables. Based on these rules, we have implemented a syllabificationalgorithm that allows segmentation of a given phoneme stream into syllables and subsequently visyllables. Secondly,we have recorded the database of visyllables using a facial motion capture system. The recorded visyllableunits are post-processed semi-automatically to ensure continuity at the vowel boundaries of the visyllables. We defineeach visyllable in terms of the Facial Movement Parameters (FMP). The FMPs are obtained as a result of thestatistical analysis of the facial motion capture data. The FMPs allow a compact representation of the visyllables.Further, the FMPs also facilitate the formulation of rules for boundary matching and smoothing after concatenatingthe visyllables units. Ours is the first visyllable based speech animation system. The proposed technique iseasy to implement, effective for real-time as well as non real-time applications and results into realistic speechanimation. Categories and Subject Descriptors (according to ACM CCS): 1.3.7 [Computer Graphics]: Three-Dimensional Graphics and Realism [source] A new method for the gradient-based optimization of molecular complexesJOURNAL OF COMPUTATIONAL CHEMISTRY, Issue 9 2009Jan Fuhrmann Abstract We present a novel method for the local optimization of molecular complexes. This new approach is especially suited for usage in molecular docking. In molecular modeling, molecules are often described employing a compact representation to reduce the number of degrees of freedom. This compact representation is realized by fixing bond lengths and angles while permitting changes in translation, orientation, and selected dihedral angles. Gradient-based energy minimization of molecular complexes using this representation suffers from well-known singularities arising during the optimization process. We suggest an approach new in the field of structure optimization that allows to employ gradient-based optimization algorithms for such a compact representation. We propose to use exponential mapping to define the molecular orientation which facilitates calculating the orientational gradient. To avoid singularities of this parametrization, the local minimization algorithm is modified to change efficiently the orientational parameters while preserving the molecular orientation, i.e. we perform well-defined jumps on the objective function. Our approach is applicable to continuous, but not necessarily differentiable objective functions. We evaluated our new method by optimizing several ligands with an increasing number of internal degrees of freedom in the presence of large receptors. In comparison to the method of Solis and Wets in the challenging case of a non-differentiable scoring function, our proposed method leads to substantially improved results in all test cases, i.e. we obtain better scores in fewer steps for all complexes. © 2008 Wiley Periodicals, Inc. J Comput Chem, 2009 [source] Automatic appearance-based loop detection from three-dimensional laser data using the normal distributions transformJOURNAL OF FIELD ROBOTICS (FORMERLY JOURNAL OF ROBOTIC SYSTEMS), Issue 11-12 2009Martin Magnusson We propose a new approach to appearance-based loop detection for mobile robots, using three-dimensional (3D) laser scans. Loop detection is an important problem in the simultaneous localization and mapping (SLAM) domain, and, because it can be seen as the problem of recognizing previously visited places, it is an example of the data association problem. Without a flat-floor assumption, two-dimensional laser-based approaches are bound to fail in many cases. Two of the problems with 3D approaches that we address in this paper are how to handle the greatly increased amount of data and how to efficiently obtain invariance to 3D rotations. We present a compact representation of 3D point clouds that is still discriminative enough to detect loop closures without false positives (i.e., detecting loop closure where there is none). A low false-positive rate is very important because wrong data association could have disastrous consequences in a SLAM algorithm. Our approach uses only the appearance of 3D point clouds to detect loops and requires no pose information. We exploit the normal distributions transform surface representation to create feature histograms based on surface orientation and smoothness. The surface shape histograms compress the input data by two to three orders of magnitude. Because of the high compression rate, the histograms can be matched efficiently to compare the appearance of two scans. Rotation invariance is achieved by aligning scans with respect to dominant surface orientations. We also propose to use expectation maximization to fit a gamma mixture model to the output similarity measures in order to automatically determine the threshold that separates scans at loop closures from nonoverlapping ones. We discuss the problem of determining ground truth in the context of loop detection and the difficulties in comparing the results of the few available methods based on range information. Furthermore, we present quantitative performance evaluations using three real-world data sets, one of which is highly self-similar, showing that the proposed method achieves high recall rates (percentage of correctly identified loop closures) at low false-positive rates in environments with different characteristics. © 2009 Wiley Periodicals, Inc. [source] A Kronecker product approximate preconditioner for SANsNUMERICAL LINEAR ALGEBRA WITH APPLICATIONS, Issue 8-9 2004Amy N. Langville Abstract Many very large Markov chains can be modelled efficiently as stochastic automata networks (SANs). A SAN is composed of individual automata which, for the most part, act independently, requiring only infrequent interaction. SANs represent the generator matrix Q of the underlying Markov chain compactly as the sum of Kronecker products of smaller matrices. Thus, storage savings are immediate. The benefit of a SAN's compact representation, known as the descriptor, is often outweighed by its tendency to make analysis of the underlying Markov chain tough. While iterative or projections methods have been used to solve the system ,Q=0, the time until these methods converge to the stationary solution , is still unsatisfactory. SAN's compact representation has made the next logical research step of preconditioning thorny. Several preconditioners for SANs have been proposed and tested, yet each has enjoyed little or no success. Encouraged by the recent success of approximate inverses as preconditioners, we have explored their potential as SAN preconditioners. One particularly relevant finding on approximate inverse preconditioning is the nearest Kronecker product approximation discovered by Pitsianis and Van Loan. In this paper, we extend the nearest Kronecker product technique to approximate the Q matrix for an SAN with a Kronecker product, A1 , A2 ,,, AN. Then, we take M = A , A ,,, A as our SAN NKP preconditioner. Copyright © 2004 John Wiley & Sons, Ltd. [source] Exploiting statistical properties of wavelet coefficient for face detection and recognitionPROCEEDINGS IN APPLIED MATHEMATICS & MECHANICS, Issue 1 2007Naseer Al-Jawad Wavelet transforms (WT) are widely accepted as an essential tool for image processing and analysis. Image and video compression, image watermarking, content-base image retrieval, face recognition, texture analysis, and image feature extraction are all but few examples. It provides an alternative tool for short time analysis of quasi-stationary signals, such as speech and image signals, in contrast to the traditional short-time Fourier transform. The Discrete Wavelet Transform (DWT) is a special case of the WT, which provides a compact representation of a signal in the time and frequency domain. In particular, wavelet transforms are capable of representing smooth patterns as well anomalies (e.g. edges and sharp corners) in images. We are focusing here on using wavelet transforms statistical properties for facial feature detection, which allows us to extract the image facial feature/edges easily. Wavelet sub-bands segmentation method been developed and used to clean up the non-significant wavelet coefficients in wavelet sub-band (k) based on the (k-1) sub-band. Moreover, erosion which is considered as one of the fundamental operation in morphological image processing, been used to reduce the unwanted edges in certain directions. For face detection, face template profiles been built for both the face and the eyes for different wavelet sub-band levels to achieve better computational performance, these profiles used to match the extracted profiles from the wavelet domain of the input image using the Dynamic Time Warping technique DTW. The DTW smallest distance allows identifying the face and the eyes location. The performance of face features distances and ratio has been also tested for face verification purposes. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source] | ||||||||||