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  • Interactive Terrain Simulation and Force Distribution Models in Sand Piles

    Pla Castells, M.; García Fernández, I.; Martínez Durá, R. J.

    (2006). Article

    Lecture Notes on Computer Science, 2006, 4173, 392-401 This paper presents an application of Cellular Automata in the field of dry Granular Systems modelling. While the study of granular systems is not a recent field, no efficient models exist, from a computational point of view, in classical methodologies. Some previous works showed that the use of Cellular Automata is suitable for the development of models that can be used in real time applications. This paper extends the existing Cellular Automata models in order to make them interactive. A model for the reaction to external forces and a pressure distribution model are presented and analyzed, with numerical examples and simulations.

  • Low-rate reduced complexity Image compression using Directionlets

    Velisavljevic, V.; Beferull-Lozano, B.; Vetterli, M.; Dragotti, P. L.

    (2006). Article

    The standard separable two-dimensional (2-D) wavelet transform (WT) has recently achieved a great success in image processing because it provides a sparse representation of smooth images. However, it fails to capture efficiently one-dimensional (1-D) discontinuities, like edges and contours, that are anisotropic and characterized by geometrical regularity along different directions. In our previous work, we proposed a construction of critically sampled perfect reconstruction anisotropic transform with directional vanishing moments (DVM) imposed in the corresponding basis functions, called directionlets. Here, we show that the computational complexity of our transform is comparable to the...

    The standard separable two-dimensional (2-D) wavelet transform (WT) has recently achieved a great success in image processing because it provides a sparse representation of smooth images. However, it fails to capture efficiently one-dimensional (1-D) discontinuities, like edges and contours, that are anisotropic and characterized by geometrical regularity along different directions. In our previous work, we proposed a construction of critically sampled perfect reconstruction anisotropic transform with directional vanishing moments (DVM) imposed in the corresponding basis functions, called directionlets. Here, we show that the computational complexity of our transform is comparable to the complexity of the standard 2-D WT and substantially lower than the complexity of other similar approaches. We also present a zerotree-based image compression algorithm using directionlets that strongly outperforms the corresponding method based on the standard wavelets at low bit rates.

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  • Lossy Network Correlated Data Gathering with High Resolution Coding

    Cristescu, R.; Beferull-Lozano, B.

    (2006). Article

    Sensor networks measuring correlated data are considered, where the task is to gather data from the network nodes to a sink. A specific scenario is addressed, where data at nodes are lossy coded with high-resolution, and the information measured by the nodes has to be reconstructed at the sink within both certain total and individual distortion bounds. The first problem considered is to find the optimal transmission structure and the rate-distortion allocations at the various spatially located nodes, such as to minimize the total power consumption cost of the network, by assuming fixed nodes positions. The optimal transmission structure is the shortest path tree and the problems of rate and...

    Sensor networks measuring correlated data are considered, where the task is to gather data from the network nodes to a sink. A specific scenario is addressed, where data at nodes are lossy coded with high-resolution, and the information measured by the nodes has to be reconstructed at the sink within both certain total and individual distortion bounds. The first problem considered is to find the optimal transmission structure and the rate-distortion allocations at the various spatially located nodes, such as to minimize the total power consumption cost of the network, by assuming fixed nodes positions. The optimal transmission structure is the shortest path tree and the problems of rate and distortion allocation separate in the high-resolution case, namely, first the distortion allocation is found as a function of the transmission structure, and second, for a given distortion allocation, the rate allocation is computed. The second problem addressed is the case when the node positions can be chosen, by finding the optimal node placement for two different targets of interest, namely total power minimization and network lifetime maximization. Finally, a node placement solution that provides a tradeoff between the two metrics is proposed.

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  • Rotation-Invariant Texture Retrieval with Gaussianized Steerable Pyramids

    Tzagkarakis, G.; Beferull-Lozano, B.; Tsakalides, P.

    (2006). Article

    This paper presents a novel rotation-invariant image retrieval scheme based on a transformation of the texture information via a steerable pyramid. First, we fit the distribution of the subband coefficients using a joint alpha-stable sub-Gaussian model to capture their non-Gaussian behavior. Then, we apply a normalization process in order to Gaussianize the coefficients. As a result, the feature extraction step consists of estimating the covariances between the normalized pyramid coefficients. The similarity between two distinct texture images is measured by minimizing a rotation-invariant version of the Kullback-Leibler Divergence between their corresponding multivariate Gaussian...

    This paper presents a novel rotation-invariant image retrieval scheme based on a transformation of the texture information via a steerable pyramid. First, we fit the distribution of the subband coefficients using a joint alpha-stable sub-Gaussian model to capture their non-Gaussian behavior. Then, we apply a normalization process in order to Gaussianize the coefficients. As a result, the feature extraction step consists of estimating the covariances between the normalized pyramid coefficients. The similarity between two distinct texture images is measured by minimizing a rotation-invariant version of the Kullback-Leibler Divergence between their corresponding multivariate Gaussian distributions, where the minimization is performed over a set of rotation angles.

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  • Directionlets: Anisotropic Multi-directional Representation with separable filtering

    Velisavijevic, V.; Beferull-Lozano, B.; Vetterli, M.; Dragotti, P. L.

    (2006). Article

    In spite of the success of the standard wavelet transform (WT) in image processing, the efficiency of its representation is limited by the spatial isotropy of its basis functions built in only horizontal and vertical directions. One-dimensional (1-D) discontinuities in images (edges and contours), which are very important elements in visual perception, intersect too many wavelet basis functions and reduce the sparsity of the representation. To capture efficiently these anisotropic geometrical structures, a more complex multi-directional (M-DIR) and anisotropic transform is required. We present a new lattice-based perfect reconstruction and critically sampled anisotropic M-DIR WT (with the...

    In spite of the success of the standard wavelet transform (WT) in image processing, the efficiency of its representation is limited by the spatial isotropy of its basis functions built in only horizontal and vertical directions. One-dimensional (1-D) discontinuities in images (edges and contours), which are very important elements in visual perception, intersect too many wavelet basis functions and reduce the sparsity of the representation. To capture efficiently these anisotropic geometrical structures, a more complex multi-directional (M-DIR) and anisotropic transform is required. We present a new lattice-based perfect reconstruction and critically sampled anisotropic M-DIR WT (with the corresponding basis functions called directionlets) that retains the separable filtering and simple filter design from the standard two-dimensional (2-D) WT and imposes directional vanishing moments (DVM). Further-more, we show that this novel transform has non-linear approximation efficiency competitive to the other previously proposed over-sampled transform constructions.

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  • Lattice Sensor Networks: Capacity Limits and Optimal Routing

    Barrenetxea, G.; Beferull-Lozano, B.; Vetterli, M.

    (2006). Article

    Lattice networks are widely used in regular settings like grid computing, distributed control, satellite constellations, and sensor networks. Thus, limits on capacity, optimal routing policies, and performance with finite buffers are key issues and are addressed in this paper. In particular, we study the routing algorithms that achieve the maximum rate per node for infinite and finite buffers in the nodes and different communication models, namely uniform communications, central data gathering and border data gathering. In the case of nodes with infinite buffers, we determine the capacity of the network and we characterize the set of optimal routing algorithms that achieve capacity. In the...

    Lattice networks are widely used in regular settings like grid computing, distributed control, satellite constellations, and sensor networks. Thus, limits on capacity, optimal routing policies, and performance with finite buffers are key issues and are addressed in this paper. In particular, we study the routing algorithms that achieve the maximum rate per node for infinite and finite buffers in the nodes and different communication models, namely uniform communications, central data gathering and border data gathering. In the case of nodes with infinite buffers, we determine the capacity of the network and we characterize the set of optimal routing algorithms that achieve capacity. In the case of nodes with finite buffers, we approximate the queue network problem and obtain the distribution on the queue size at the nodes. This distribution allows us to study the effect of routing on the queue distribution and derive the algorithms that achieve the maximum rate.

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  • Power-Efficient Sensor Placement and Transmission Structure for Data Gathering under Distortion Constraints

    Ganesan, D.; Cristescu, R.; Beferull-Lozano, B.

    (2006). Article

    We consider the joint optimization of sensor placement and transmission structure for data gathering, where a given number of nodes need to be placed in a field such that the sensed data can be reconstructed at a sink within specified distortion bounds while minimizing the energy consumed for communication. We assume that the nodes use joint entropy coding based on explicit communication between sensor nodes, and consider both maximum and average distortion bounds. The optimization is complex since it involves an interplay between the spaces of possible transmission structures given radio reachability limitations, and feasible placements satisfying distortion bounds. We address this problem...

    We consider the joint optimization of sensor placement and transmission structure for data gathering, where a given number of nodes need to be placed in a field such that the sensed data can be reconstructed at a sink within specified distortion bounds while minimizing the energy consumed for communication. We assume that the nodes use joint entropy coding based on explicit communication between sensor nodes, and consider both maximum and average distortion bounds. The optimization is complex since it involves an interplay between the spaces of possible transmission structures given radio reachability limitations, and feasible placements satisfying distortion bounds. We address this problem by first looking at the simplified problem of optimal placement in the one-dimensional case. An analytical solution is derived for the case when there is a simple aggregation scheme, and numerical results are provided for the cases when joint entropy encoding is used. We use the insight from our 1-D analysis to extend our results to the 2-D case, and show that our algorithm for two-dimensional placement and transmission structure provides significant power benefit over a commonly used combination of uniformly random placement and shortest path trees.

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  • Oversampled A/D Conversion and Error-Rate Dependence of Non-Bandlimited Signals with Finite Rate of Innovation

    Jovanovic, I.; Beferull-Lozano, B.

    (2006). Article

    We study the problem of A/D conversion and error-rate dependence of a class of nonbandlimited signals with finite rate of innovation. In particular, we analyze a continuous periodic stream of Diracs, characterized by a finite set of time positions and weights. Previous research has only considered sampling of this type of signals, ignoring the presence of quantization, necessary for any practical implementation. To this end, we first define the concept of consistent reconstruction and introduce corresponding oversampling in both time and frequency. High accuracy in a consistent reconstruction is achieved by enforcing the reconstructed signal to satisfy three sets of constraints, related to...

    We study the problem of A/D conversion and error-rate dependence of a class of nonbandlimited signals with finite rate of innovation. In particular, we analyze a continuous periodic stream of Diracs, characterized by a finite set of time positions and weights. Previous research has only considered sampling of this type of signals, ignoring the presence of quantization, necessary for any practical implementation. To this end, we first define the concept of consistent reconstruction and introduce corresponding oversampling in both time and frequency. High accuracy in a consistent reconstruction is achieved by enforcing the reconstructed signal to satisfy three sets of constraints, related to low-pass filtering, quantization and the space of continuous periodic streams of Diracs. We provide two schemes to reconstruct the signal. For the first one, we prove that the estimation mean squared error of the time positions is O(1/Rt2Rf3), where Rt and Rf are the oversampling ratios in time and frequency, respectively. For the second scheme, it is experimentally observed that, at the cost of higher complexity, the estimation accuracy lowers to O(1/Rt2Rf5). Our experimental results show a clear advantage of consistent over nonconsistent reconstruction. Regarding the rate, we consider a threshold crossing based scheme where, as opposed to previous research, both oversampling in time and in frequency influence the coding rate. We compare the error-rate behavior resulting, on the one hand, from increasing the oversampling in time and/or frequency, and, on the other hand, from decreasing the quantization stepsize.

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  • Network Correlated Data Gathering with Explicit Communication: NP-Completeness and Algorithms

    Cristescu, R.; Beferull-Lozano, B.; Vetterli, M.; Wattenhofer, R.

    (2006). Article

    We consider the problem of correlated data gathering by a network with a sink node and a tree-based communication structure, where the goal is to minimize the total transmission cost of transporting the information collected by the nodes, to the sink node. For source coding of correlated data, we consider a joint entropy-based coding model with explicit communication where coding is simple and the transmission structure optimization is difficult. We first formulate the optimization problem definition in the general case and then we study further a network setting where the entropy conditioning at nodes does not depend on the amount of side information, but only on its availability. We prove...

    We consider the problem of correlated data gathering by a network with a sink node and a tree-based communication structure, where the goal is to minimize the total transmission cost of transporting the information collected by the nodes, to the sink node. For source coding of correlated data, we consider a joint entropy-based coding model with explicit communication where coding is simple and the transmission structure optimization is difficult. We first formulate the optimization problem definition in the general case and then we study further a network setting where the entropy conditioning at nodes does not depend on the amount of side information, but only on its availability. We prove that even in this simple case, the optimization problem is NP-hard. We propose some efficient, scalable, and distributed heuristic approximation algorithms for solving this problem and show by numerical simulations that the total transmission cost can be significantly improved over direct transmission or the shortest path tree. We also present an approximation algorithm that provides a tree transmission structure with total cost within a constant factor from the optimal.

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  • IADAT-micv2005. International Conference on Multimedia, Image Processing and Computer Vision: A 3D environment for driving simulation scenario design & evaluation

    coma, Inmaculada; Fernández, Marcos; Vera, Lucía; Olanda, Ricardo

    (2005). Article

    Simulation and virtual environments are used increasingly for training and behaviour evaluation purposes. Driving simulators are a specific case of these systems. They have been proof as effective tools for drivers training, risky driving styles evaluation or the evaluation of the effects of external factors or new technologies in driving task. The interest in behaviour evaluation and training of drivers makes it necessary to design experiments that provide measurements of driver’s actions. These experiments are usually dynamic scenarios, which can be defined as a set of dynamic elements (cars, lights, pedestrians, etc.) carrying out some tasks in a synchronized way. The purpose of these...

    Simulation and virtual environments are used increasingly for training and behaviour evaluation purposes. Driving simulators are a specific case of these systems. They have been proof as effective tools for drivers training, risky driving styles evaluation or the evaluation of the effects of external factors or new technologies in driving task. The interest in behaviour evaluation and training of drivers makes it necessary to design experiments that provide measurements of driver’s actions. These experiments are usually dynamic scenarios, which can be defined as a set of dynamic elements (cars, lights, pedestrians, etc.) carrying out some tasks in a synchronized way. The purpose of these scenarios is to force the driver to make a decision.

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