A system for learning statistical motion patterns

Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, where objects move in predefined ways. It is highly desirable to automatically construct object motion patterns which reflect the knowledge of the scene. In this paper, we present a system for automatically learning motion patterns for anomaly detection and behavior prediction based on a proposed algorithm for robustly tracking multiple objects. In the tracking algorithm, foreground pixels are clustered using a fast accurate fuzzy k-means algorithm. Growing and prediction of the cluster centroids of foreground pixels ensure that each cluster centroid is associated with a moving object in the scene. In the algorithm for learning motion patterns, trajectories are clustered hierarchically using spatial and temporal information and then each motion pattern is represented with a chain of Gaussian distributions. Based on the learned statistical motion patterns, statistical methods are used to detect anomalies and predict behaviors. Our system is tested using image sequences acquired, respectively, from a crowded real traffic scene and a model traffic scene. Experimental results show the robustness of the tracking algorithm, the efficiency of the algorithm for learning motion patterns, and the encouraging performance of algorithms for anomaly detection and behavior prediction

Evidence for the band broadening across the ferromagnetic transition in Cr1/3_{1/3}NbSe2_2

The electronic structure of Cr$_{1/3}$NbSe$_2$ is studied via optical spectroscopy. We observe two low-energy interband transitions in the paramagnetic phase, which split into four peaks as the compound enters the ferromagnetic state. The band structure calculation indicates the four peaks are interband transitions to the spin up Cr e$_g$ states. We show that the peak splitting below the Curie temperature is \emph{not} due to the exchange splitting of spin up and down bands, but directly reflects a band broadening effect in Cr-derived states upon the spontaneous ferromagnetic ordering.Comment: 6 pages, 5 figures, to be published in Phys. Rev.

A system for learning statistical motion patterns

Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, where objects move in predefined ways. It is highly desirable to automatically construct object motion patterns which reflect the knowledge of the scene. In this paper, we present a system for automatically learning motion patterns for anomaly detection and behavior prediction based on a proposed algorithm for robustly tracking multiple objects. In the tracking algorithm, foreground pixels are clustered using a fast accurate fuzzy k-means algorithm. Growing and prediction of the cluster centroids of foreground pixels ensure that each cluster centroid is associated with a moving object in the scene. In the algorithm for learning motion patterns, trajectories are clustered hierarchically using spatial and temporal information and then each motion pattern is represented with a chain of Gaussian distributions. Based on the learned statistical motion patterns, statistical methods are used to detect anomalies and predict behaviors. Our system is tested using image sequences acquired, respectively, from a crowded real traffic scene and a model traffic scene. Experimental results show the robustness of the tracking algorithm, the efficiency of the algorithm for learning motion patterns, and the encouraging performance of algorithms for anomaly detection and behavior prediction

The Structure of Structure Formation Theories

We study the general structure of models for structure formation, with applications to the reverse engineering of the model from observations. Through a careful accounting of the degrees of freedom in covariant gravitational instability theory, we show that the evolution of structure is completely specified by the stress history of the dark sector. The study of smooth, entropic, sonic, scalar anisotropic, vector anisotropic, and tensor anisotropic stresses reveals the origin, robustness, and uniqueness of specific model phenomenology. We construct useful and illustrative analytic solutions that cover cases with multiple species of differing equations of state relevant to the current generation of models, especially those with effectively smooth components. We present a simple case study of models with phenomenologies similar to that of a LambdaCDM model to highlight reverse-engineering issues. A critical-density universe dominated by a single type of dark matter with the appropriate stress history can mimic a LambdaCDM model exactly.Comment: 31 pages, 18 figures, RevTeX, submitted to Phys. Rev.

Constraining the time variation of the coupling constants from cosmic microwave background: effect of \Lambda_{QCD}

We investigate constraints on the time variation of the fine structure constant between the recombination epoch and the present epoch, \Delta\alpha/\alpha \equiv (\alpha_{rec} - \alpha_{now})/\alpha_{now}, from cosmic microwave background (CMB) taking into account simultaneous variation of other physical constants, namely the electron mass m_{e} and the proton mass m_{p}. In other words, we consider the variation of Yukawa coupling and the QCD scale \Lambda_{QCD} in addition to the electromagnetic coupling. We clarify which parameters can be determined from CMB temperature anisotropy in terms of singular value decomposition. Assuming a relation among variations of coupling constants governed by a single scalar field (the dilaton), the 95% confidence level (C.L.) constraint on \Delta\alpha/\alpha is found to be -8.28 \times 10^{-3} < \Delta\alpha/\alpha < 1.81 \times 10^{-3}, which is tighter than the one obtained by considering only the change of \alpha and m_{e}. We also obtain the constraint on the time variation of the proton-to-electron mass ratio \mu \equiv m_{p}/m_{e} to be -0.52 < \Delta\mu/\mu < 0.17 (95% C.L.) under the same assumption. Finally, we also implement a forecast for constraints from the PLANCK survey.Comment: 25 pages, 4 figures; references adde

Atom clusters and vibrational excitations in chemically-disordered Pt357Fe

Inelastic nuclear resonant scattering spectra of Fe-57 atoms were measured on crystalline alloys of Pt3Fe-57 that were chemically disordered, partially ordered, and L1(2) ordered. Phonon partial density of states curves for Fe-57 were obtained from these spectra. Upon disordering, about 10% of the spectral intensity underwent a distinct shift from 25 to 19 meV. This change in optical modes accounted for most of the change of the vibrational entropy of disordering contributed by Fe atoms, which was (+0.10 +/- 0.03) k(B) (Fe atom)(-1). Prospects for parametrizing the vibrational entropy with low-order cluster variables were assessed. To calculate the difference in vibrational entropy of the disordered and ordered alloys, the clusters must be large enough to account for the abundances of several of the atom configurations of the first-nearest-neighbor shell about the Fe-57 atoms

M-atom conductance oscillations of a metallic quantum wire

The electron transport through a monoatomic metallic wire connected to leads is investigated using the tight-binding Hamiltonian and Green's function technique. Analytical formulas for the transmittance are derived and M-atom oscillations of the conductance versus the length of the wire are found. Maxima of the transmittance function versus the energy, for the wire consisted of N atoms, determine the (N+1) period of the conductance. The periods of conductance oscillations are discussed and the local and average quantum wire charges are presented. The average charge of the wire is linked with the period of the conductance oscillations and it tends to the constant value as the length of the wire increases. For M-atom periodicity there are possible (M-1) average occupations of the wire states.Comment: 8 pages, 5 figures. J.Phys.: Condens. matter (2005) accepte