8,556 research outputs found
Distributed Maximum Likelihood for Simultaneous Self-localization and Tracking in Sensor Networks
We show that the sensor self-localization problem can be cast as a static
parameter estimation problem for Hidden Markov Models and we implement fully
decentralized versions of the Recursive Maximum Likelihood and on-line
Expectation-Maximization algorithms to localize the sensor network
simultaneously with target tracking. For linear Gaussian models, our algorithms
can be implemented exactly using a distributed version of the Kalman filter and
a novel message passing algorithm. The latter allows each node to compute the
local derivatives of the likelihood or the sufficient statistics needed for
Expectation-Maximization. In the non-linear case, a solution based on local
linearization in the spirit of the Extended Kalman Filter is proposed. In
numerical examples we demonstrate that the developed algorithms are able to
learn the localization parameters.Comment: shorter version is about to appear in IEEE Transactions of Signal
Processing; 22 pages, 15 figure
Cross-calibration of Time-of-flight and Colour Cameras
Time-of-flight cameras provide depth information, which is complementary to
the photometric appearance of the scene in ordinary images. It is desirable to
merge the depth and colour information, in order to obtain a coherent scene
representation. However, the individual cameras will have different viewpoints,
resolutions and fields of view, which means that they must be mutually
calibrated. This paper presents a geometric framework for this multi-view and
multi-modal calibration problem. It is shown that three-dimensional projective
transformations can be used to align depth and parallax-based representations
of the scene, with or without Euclidean reconstruction. A new evaluation
procedure is also developed; this allows the reprojection error to be
decomposed into calibration and sensor-dependent components. The complete
approach is demonstrated on a network of three time-of-flight and six colour
cameras. The applications of such a system, to a range of automatic
scene-interpretation problems, are discussed.Comment: 18 pages, 12 figures, 3 table
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