Correlated electron-ion dynamics: the excitation of atomic motion by energetic electrons

Correlated electron-ion dynamics (CEID) is an extension of molecular dynamics that allows us to introduce in a correct manner the exchange of energy between electrons and ions. The formalism is based on a systematic approximation: small amplitude moment expansion. This formalism is extended here to include the explicit quantum spread of the ions and a generalization of the Hartree-Fock approximation for incoherent sums of Slater determinants. We demonstrate that the resultant dynamical equations reproduce analytically the selection rules for inelastic electron-phonon scattering from perturbation theory, which control the mutually driven excitations of the two interacting subsystems. We then use CEID to make direct numerical simulations of inelastic current-voltage spectroscopy in atomic wires, and to exhibit the crossover from ionic cooling to heating as a function of the relative degree of excitation of the electronic and ionic subsystems.

The visual processing of motion-defined transparency

Our understanding of how the visual system processes motion transparency, the phenomenon by which multiple directions of motion are perceived to co-exist in the same spatial region, has grown considerably in the past decade. There is compelling evidence that the process is driven by global-motion mechanisms. Consequently, although transparently moving surfaces are readily segmented over an extended space, the visual system cannot separate two motion signals that co-exist in the same local region. A related issue is whether the visual system can detect transparently moving surfaces simultaneously, or whether the component signals encounter a serial â??bottleneckâ?? during their processing? Our initial results show that, at sufficiently short stimulus durations, observers cannot accurately detect two superimposed directions; yet they have no difficulty in detecting one pattern direction in noise, supporting the serial-bottleneck scenario. However, in a second experiment, the difference in performance between the two tasks disappears when the component patterns are segregated. This discrepancy between the processing of transparent and non-overlapping patterns may be a consequence of suppressed activity of global-motion mechanisms when the transparent surfaces are presented in the same depth plane. To test this explanation, we repeated our initial experiment while separating the motion components in depth. The marked improvement in performance leads us to conclude that transparent motion signals are represented simultaneously.

Fractal rotation isolates mechanisms for form-dependent motion in human vision

Here, we describe a motion stimulus in which the quality of rotation is fractal. This makes its motion unavailable to the translationbased motion analysis known to underlie much of our motion perception. In contrast, normal rotation can be extracted through the aggregation of the outputs of translational mechanisms. Neural adaptation of these translation-based motion mechanisms is thought to drive the motion after-effect, a phenomenon in which prolonged viewing of motion in one direction leads to a percept of motion in the opposite direction. We measured the motion after-effects induced in static and moving stimuli by fractal rotation. The after-effects found were an order of magnitude smaller than those elicited by normal rotation. Our findings suggest that the analysis of fractal rotation involves different neural processes than those for standard translational motion. Given that the percept of motion elicited by fractal rotation is a clear example of motion derived from form analysis, we propose that the extraction of fractal rotation may reflect the operation of a general mechanism for inferring motion from changes in form.

Approach to automatic video motion segmentation

A novel, fast automatic motion segmentation approach is presented. It differs from conventional pixel or edge based motion segmentation approaches in that the proposed method uses labelled regions (facets) to segment various video objects from the background. Facets are clustered into objects based on their motion and proximity details using Bayesian logic. Because the number of facets is usually much lower than the number of edges and points, using facets can greatly reduce the computational complexity of motion segmentation. The proposed method can tackle efficiently the complexity of video object motion tracking, and offers potential for real-time content-based video annotation.

Low-power systolic array processor architecture for FSBM video motion estimation

A novel power-efficient systolic array architecture is proposed for full search block matching (FSBM) motion estimation, where the partial distortion elimination algorithm is used to dynamically switch off the computation of eliminated partial candidate blocks. The RTL-level simulation shows that the proposed architecture can reduce the power consumption of the computation part of the algorithm to about 60% of that of the conventional 2D systolic arrays.

Reconfigurable video Motion Estimation processor

In this paper, a new reconfigurable multi-standard Motion Estimation (ME) architecture is proposed and a standard-cell based design study is presented. The architecture exhibits simpler control, high throughput and relative low hardware cost and is highly competitive when compared with existing designs for specific video standards. ©2007 IEEE.