This paper presents a numerical method for the determination of the identifiable parameters of parallel robots. The special case of Stewart-Gough 6 degrees-offreedom parallel robots is studied for classical and self calibration methods, but this method can be generalized to any kind of parallel robot. The method is based on QR decomposition of the observation matrix of the calibration system. N...

This paper presents a self-calibration and pose estimation method that uses two cameras which only diier by focal length. The estimation of the rotation and focal lengths is independent of the translation recovery. Unlike most methods, we do not initialize our recovery with the projective camera. Instead we estimate the ego-motion and calibration from 3 homographies. These homographies can be e...

Many computer vision problems (e.g. the estimation of the fundamental matrix, the homography matrix, or camera calibration as well as the factorization method) belong to the class of subspace problems which are well-known in signal processing. They essentially consist in dividing a vector space into a lower dimensional data space and an orthogonal error space, based on the information available...

prediction using pure standards is expected to be biased whenever the slope of the calibration is affected by the presence of sample matrix. moreover, in the presence of unknown spectral interferents, first-order algorithms like partial least squares cannot be used. in this study, a method for determination of carvedilol (car) in tablet and urine samples is proposed by excitation-emission fluor...

Introduction: Previously, we presented a new autocalibrating parallel imaging (acPI) method that does not explicitly require autocalibration lines and is based on low-rank matrix completion [7]. This time, we extend this technique to nonCartesian trajectories. Our method jointly autocalibrates and reconstructs the images, similarly to other joint estimation (coil & data) techniques [2-5]. Howev...

The quantitation of target analytes in complex matrices such as biological samples requires special calibration approaches to compensate for additional capacity or activity in the matrix samples. A conventional calibration curve, obtained with standard solutions, is one of the most important calibration procedures for quantitation of target analytes in such matrices. However, these technique re...

Extrinsic calibration of a camera and a 2D laser range finder (lidar) sensors is crucial in sensor data fusion applications; for example SLAM algorithms used in mobile robot platforms. The fundamental challenge of extrinsic calibration is when the camera-lidar sensors do not overlap or share the same field of view. In this paper we propose a novel and flexible approach for the extrinsic calibra...

In recent years, the research field on smart environments, which are spaces with multiple embedded and networked sensors and actuators, has been expanding (Cook & Das, 2004). The main purpose for the introduction of smart environments is to support humans in both physical and informative ways (Johanson et al., 2002), (Mynatt et al., 2004), (Mizoguchi et al., 1999). In smart environments, the di...

The stochastic multicloud model (SMCM) was recently developed (Khouider, Biello, and Majda, 2010) to represent the missing variability in general circulation models due to unresolved features of organized tropical convection. This research aims at finding a robust calibration methodology for the SMCM to estimate key model parameters from data. We formulate the calibration problem within a Bayes...