Analysis of distributed fusion alternatives in coordinated vision agents

6 pages, 10 figures.-- Contributed to: 11th International Conference on Information Fusion (FUSION'2008, Cologne, Germany, Jun 30-Jul 3, 2008).In this paper, we detail some technical alternatives when building a coherent distributed visual sensor network by using the multi-agent paradigm. We argue that the multi-agent paradigm fits well within the visual sensor network architecture and in this paper we specially focus on the problem of distributed data fusion. Three different data fusion coordination schemes are proposed and experimental results of passive fusion are presented and discussed. The main contributions of this paper are twofold, first we propose the use of multi-agent paradigm as the visual sensor architecture and present a real system results. Secondly, the use of feedback information in the visual sensors, called active fusion, is proposed. The experimental results prove that the multi-agent paradigm fits well within the visual sensor network and provide a novel mechanism to develop a real visual sensor network system.This work was partially supported by projects MADRINET, TEC2005-07186-C03-02, SINPROB, TSI2005-07344-C02-02.Publicad

Distributed Greedy Sensor Scheduling for Model-based Reconstruction of Space-Time Continuous Physical Phenomena

A novel distributed sensor scheduling method for large-scale sensor networks observing space-time continuous physical phenomena is introduced. In a first step, the model of the distributed phenomenon is spatially and temporally decomposed leading to a linear probabilistic finite-dimensional model. Based on this representation, the information gain of sensor measurements is evaluated by means of the so-called covariance reduction function. For this reward function, it is shown that the performance of the greedy sensor scheduling is at least half that of the optimal scheduling considering long-term effects. This finding is the key for distributed sensor scheduling, where a central processing unit or fusion center is unnecessary, and thus, scaling as well as reliability is ensured. Hence, greedy scheduling in combination with a proposed hierarchical communication scheme requires only local sensor information and communication

Robust sensor fusion in real maritime surveillance scenarios

8 pages, 14 figures.-- Proceedings of: 13th International Conference on Information Fusion (FUSION'2010), Edinburgh, Scotland, UK, Jul 26-29, 2010).This paper presents the design and evaluation of a sensor fusion system for maritime surveillance. The system must exploit the complementary AIS-radar sensing technologies to synthesize a reliable surveillance picture using a highly efficient implementation to operate in dense scenarios. The paper highlights the realistic effects taken into account for robust data combination and system scalability.This work was supported in part by a national project with NUCLEO CC, and research projects CICYT TEC2008-06732-C02-02/TEC, CICYT TIN2008-06742-C02-02/TSI, SINPROB, CAM CONTEXTS S2009/TIC-1485 and DPS2008-07029-C02-02.Publicad

Simultaneous State and Parameter Estimation for Physics-Based Tracking of Heart Surface Motion

Most existing approaches for tracking of the beating heart motion assume known cardiac kinematics and material parameters. However, these assumptions are not realistic for application in beating heart surgery. In this paper, a novel probabilistic tracking approach based on a physical model of the heart surface is presented. In contrast to existing approaches, the physical information about heart kinematics and material properties is incorporated and considered in an estimation of the heart behavior. An additional advantage is that the time-dependencies and uncertainties of the heart parameters are efficiently handled by exploiting simultaneous state and parameter estimation. Furthermore, by decomposing the state into linear and nonlinear substructures, the computational complexity of the estimation problem is reduced. The experimental results demonstrate the high performance of the method proposed in this paper. The solution of the parameter identification problem allows a personalized physical model and opens up possibilities to apply the physics-based tracking of the heart surface motion in a clinical environment

The Sliced Gaussian Mixture Filter with Adaptive State Decomposition Depending on Linearization Error

In this paper, a novel nonlinear/non-linear model decomposition for the Sliced Gaussian Mixture Filter is presented. Based on the level of nonlinearity of the model, the overall estimation problem is decomposed into a severely nonlinear and a slightly nonlinear part, which are processed by different estimation techniques. To further improve the efficiency of the estimator, an adaptive state decomposition algorithm is introduced that allows decomposition according to the linearization error for nonlinear system and measurement models. Simulations show that this approach has orders of magnitude less complexity compared to other state of the art estimators, while maintaining comparable estimation errors

Geographic context configuration in fusion algorithms for maritime surveillance

Proceedings of: 17th International Conference on Information Fusion (FUSION 2014): Salamanca, Spain 7-10 July 2014.Real fusion system applications can be required to operate on wide areas for long periods of time. Adaptation is a basic capability under these circumstances. This paper presents a maritime surveillance platform designed to be flexible and robust. It features online configuration capabilities allowing to: (a) change the applied algorithms, (b) modify the operating parameters of the running algorithms, (c) tune the characterization of the available sensors. These configurations can be applied to limited spatial regions and time spans. This allows to use powerful or more specific configurations for localized scenarios (risks, clutter, alarms), or account for exceptional situations that can affect sensors, such as weather anomalies.This work was funded by contract between DEIMOS SPACE, S.L.U. and Universidad Carlos III, by Spanish Ministry of Economy and Competitiveness under grants TEC2012- 37832-C02-01, TEC2011-28626-C02-02, and by Madrid Region Gov., grant CAM CONTEXTS (S2009/TIC-1485).Publicad