Abstract:
The optical flow approach has emerged as a major technique for estimating object motion in image sequences. However, the obtained results by most optical flow techniques are poor because they are strongly affected by large illumination changes and by motion discontinuities. On the other hand, there have been two thrusts in the development of optical flow algorithms. One has emphasized higher accuracy; the other faster implementation. These two thrusts have been independently pursed, without addressing the accuracy vs. efficiency trade-offs. The optical flow computation requires high computing resources and is highly affected by changes in the illumination conditions in most of the existing techniques. In this paper, a new strategy for image sequence processing is proposed. The data reduction achieved with this strategy allows a faster optical flow computation. In addition, the proposed architecture is a hardware custom implementation in EP1S60F1020 FPGA showing the achieved performance.

Abstract:
A computational model is constrcted to explore the principles of visual motion processing from area V1 to area MT in primate visual cortex, where a significant transition from local motion detection to global integration of pattern motion takes place. The first layer of the model consists of Reichardt's elementary motion detectors (EMD), which extracts local velocity as well as structural properties of the moving pattern. Further processing is realized by the Boltzmann Machine neural network, whose learing algorithm inherits the distinctive property of local updaing. During the learning phase, the network continually revises the connection strengths to form the internal representation of the environmental structures, which have been coded on the "visible units" of the network. The structures here combine the various two dimensinal local vector fields presented and the corresponding true directions of pattern motion. Training of the network is influenced by a few netwok parameters. Generally, the behavior of the network improves with the increase of the number of presentations, showing that it is able to give the true direction of pattern motion regardless of different orientations of the moveing pattern.

Abstract:
It is shown that quantum particle detectors are not reliable probes of spacetime structure. In particular, they fail to distinguish between inertial and non-inertial motion in a general spacetime. To prove this, we consider detectors undergoing circular motion in an arbitrary static spherically symmetric spacetime, and give a necessary and sufficient condition for the response function to vanish when the field is in the static vacuum state. By examining two particular cases, we show that there is no relation, in general, between the vanishing of the response function and the fact that the detector motion is, or is not, geodesic. In static asymptotically flat spacetimes, however, all rotating detectors are excited in the static vacuum. Thus, in this particular case the static vacuum appears to be associated with a non-rotating frame. The implications of these results for the equivalence principle are considered. In particular, we discuss how to properly formulate the principle for particle detectors, and show that it is satisfied.

Abstract:
Models of computation operating over the real numbers and computing a larger class of functions compared to the class of general recursive functions invariably introduce a non-finite element of infinite information encoded in an arbitrary non-computable number or non-recursive function. In this paper we show that Turing universality is only possible at every Turing degree but not over all, in that sense universality at the first level is elegantly well defined while universality at higher degrees is at least ambiguous. We propose a concept of universal relativity and universal jump between levels in the arithmetical and analytical hierarchy.

Abstract:
It is indicated that principal models of computation are indeed significantly related. The quantum field computation model contains the quantum computation model of Feynman. (The term "quantum field computer" was used by Freedman.) Quantum field computation (as enhanced by Wightman's model of quantum field theory) involves computation over the continuum which is remarkably related to the real computation model of Smale. The latter model was established as a generalization of Turing computation. All this is not surprising since it is well known that the physics of quantum field theory (which includes Einstein's special relativity) contains quantum mechanics which in turn contains classical mechanics. The unity of these computing models, which seem to have grown largely independently, could shed new light into questions of computational complexity, into the central P (Polynomial time) versus NP (Non-deterministic Polynomial time) problem of computer science, and also into the description of Nature by fundamental physics theories.

Abstract:
We propose a construction of anyon systems associated to quantum tori with real multiplication and the embedding of quantum tori in AF algebras. These systems generalize the Fibonacci anyons, with weaker categorical properties, and are obtained from the basic modules and the real multiplication structure.

Abstract:
Starting from Borel's description of the mod-2 cohomology of real flag manifolds, we give a minimal presentation of the cohomology ring for semi complete flag manifolds $F_{k,m}:=F(1,\ldots,1,m)$ where $1$ is repeated $k$ times. The information is used in order to estimate Farber's topological complexity of these spaces when $m$ approaches (from below) a 2-power. In particular, we get almost sharp estimates for $F_{2,2^e-1}$ which resemble the known situation for the real projective spaces $F_{1,2^e}$. Our results indicate that the agreement between the topological complexity and the immersion dimension of real projective spaces no longer holds for other flag manifolds. More interestingly, we also get corresponding results for the $s$-th (higher) topological complexity of these spaces. Actually, we prove the surprising fact that, as $s$ increases, the estimates become stronger. Indeed, we get several full computations of the higher motion planning problem of these manifolds. This property is also shown to hold for surfaces: we get a complete computation of the higher topological complexity of all closed surfaces (orientable or not). A homotopy-obstruction explanation is included for the phenomenon of having a cohomologically accessible higher topological complexity even when the regular topological complexity is not so accessible.

Abstract:
Relativistically covariant equation of motion for real dust particle under the action of electromagnetic radiation is derived. The particle is neutral in charge. Equation of motion is expressed in terms of particle's optical properties, standardly used in optics for stationary particles.

Abstract:
There is a lot of redundant data for image processing in an image, in motion picture as well. The more data for image processing we have, the more time is needed for preprocessing it. That is why we need to work with important data only. In order to identify or classify motion, data processing in real time is needed.

Abstract:
We propose an implementation of quantum logic gates via virtual vibrational excitations in an ion trap quantum computer. Transition paths involving unpopulated, vibrational states interfere destructively to eliminate the dependence of rates and revolution frequencies on vibrational quantum numbers. As a consequence quantum computation becomes feasible with ions whos vibrations are strongly coupled to a thermal reservoir.