We classify and review existing algorithms for computing the fundamental matrix from point correspondences and propose new effective schemes: 7-parameter Levenberg-Marquardt (LM) search, EFNS, and EFNS-based bundle adjustment. Doing experimental comparison, we show that EFNS and the 7-parameter LM search exhibit the best performance and that additional bundle adjustment does not increase the ac...

We describe the rationale for the development of a psychophysical procedure that allows individual listeners to adjust the frequency-gain characteristic of a programmable hearing aid on a unidimensional scale, based on a target-gain reference value. The listener's task is to adjust the frequency response and select the parametric value judged to optimize the intelligibility or quality of speech...

We propose an efficient parallel bundle adjustment (BA) algorithm to refine 3D reconstruction of the large-scale structure from motion (SfM) problem, which uses image collections from Internet. Different from the latest BA techniques that improve efficiency by optimizing the reprojection error function with Conjugate Gradient (CG) methods, we employ the parameter vector partition strategy. More...

This paper proposes a control system design method by the multiobjective fuzzy satisficing approach using Genetic Algorithm (GA). First, a control system design is formulated as a constrained multiobjective optimization problem, and it is transformed into a fuzzy satisficing problem by introducing the aspiration level and the unsatisfying function. It is solved by a GA interactively. Then, the ...

Volume visualization involves the graphical processing and on-screen rendering of a volume dataset for the purposes of exploring, classifying and viewing information from the underlying data. Often, the manual adjustment of the various parameters involved in the rendering process can become a tedious task, especially given the ever increasing complexity of volume rendering applications. We atte...

Spiegelhalter and Lauritzen [15] studied se­ quential learning in Bayesian networks and proposed three models for the representation of conditional probabilities. A forth model, shown here, assumes that the parameter dis­ tribution is given by a product of Gaussian functions and updates them from the >. and 1r messages of evidence propagation. We also generalize the noisy OR-gate for multival­ ...