3 resultados para Simulated moving bed
em Massachusetts Institute of Technology
Resumo:
We describe a new method for motion estimation and 3D reconstruction from stereo image sequences obtained by a stereo rig moving through a rigid world. We show that given two stereo pairs one can compute the motion of the stereo rig directly from the image derivatives (spatial and temporal). Correspondences are not required. One can then use the images from both pairs combined to compute a dense depth map. The motion estimates between stereo pairs enable us to combine depth maps from all the pairs in the sequence to form an extended scene reconstruction and we show results from a real image sequence. The motion computation is a linear least squares computation using all the pixels in the image. Areas with little or no contrast are implicitly weighted less so one does not have to explicitly apply a confidence measure.
Resumo:
In this thesis, two different sets of experiments are described. The first is an exploration of the microscopic superfluidity of dilute gaseous Bose- Einstein condensates. The second set of experiments were performed using transported condensates in a new BEC apparatus. Superfluidity was probed by moving impurities through a trapped condensate. The impurities were created using an optical Raman transition, which transferred a small fraction of the atoms into an untrapped hyperfine state. A dramatic reduction in the collisions between the moving impurities and the condensate was observed when the velocity of the impurities was close to the speed of sound of the condensate. This reduction was attributed to the superfluid properties of a BEC. In addition, we observed an increase in the collisional density as the number of impurity atoms increased. This enhancement is an indication of bosonic stimulation by the occupied final states. This stimulation was observed both at small and large velocities relative to the speed of sound. A theoretical calculation of the effect of finite temperature indicated that collision rate should be enhanced at small velocities due to thermal excitations. However, in the current experiments we were insensitive to this effect. Finally, the factor of two between the collisional rate between indistinguishable and distinguishable atoms was confirmed. A new BEC apparatus that can transport condensates using optical tweezers was constructed. Condensates containing 10-15 million sodium atoms were produced in 20 s using conventional BEC production techniques. These condensates were then transferred into an optical trap that was translated from the âproduction chamber’ into a separate vacuum chamber: the âscience chamber’. Typically, we transferred 2-3 million condensed atoms in less than 2 s. This transport technique avoids optical and mechanical constrainsts of conventional condensate experiments and allows for the possibility of novel experiments. In the first experiments using transported BEC, we loaded condensed atoms from the optical tweezers into both macroscopic and miniaturized magnetic traps. Using microfabricated wires on a silicon chip, we observed excitation-less propagation of a BEC in a magnetic waveguide. The condensates fragmented when brought very close to the wire surface indicating that imperfections in the fabrication process might limit future experiments. Finally, we generated a continuous BEC source by periodically replenishing a condensate held in an optical reservoir trap using fresh condensates delivered using optical tweezers. More than a million condensed atoms were always present in the continuous source, raising the possibility of realizing a truly continuous atom lase.
Resumo:
A fast simulated annealing algorithm is developed for automatic object recognition. The normalized correlation coefficient is used as a measure of the match between a hypothesized object and an image. Templates are generated on-line during the search by transforming model images. Simulated annealing reduces the search time by orders of magnitude with respect to an exhaustive search. The algorithm is applied to the problem of how landmarks, for example, traffic signs, can be recognized by an autonomous vehicle or a navigating robot. The algorithm works well in noisy, real-world images of complicated scenes for model images with high information content.