Motion Pattern Extraction and Event Detection for Automatic Visual Surveillance

International audienc

Testing spherical evolution for modelling void abundances

We compare analytical predictions of void volume functions to those measured from N-body simulations, detecting voids with the zobov void finder. We push to very small, non-linear voids, below few Mpc radius, by considering the unsampled dark matter density field. We also study the case where voids are identified using haloes. We develop analytical formula for the void abundance of both the excursion set approach and the peaks formalism. These formulas are valid for random walks smoothed with a top-hat filter in real space, with a large class of realistic barrier models. We test the extent to which the spherical evolution approximation, which forms the basis of the analytical predictions, models the highly aspherical voids that occur in the cosmic web, and are found by a watershed-based algorithm such as zobov. We show that the volume function returned by zobov is quite sensitive to the choice of treatment of subvoids, a fact that has not been appreciated previously. For reasonable choices of subvoid exclusion, we find that the Lagrangian density δv of the zobov voids - which is predicted to be a constant δv≈−2.7 in the spherical evolution model - is different from the predicted value, showing substantial scatter and scale dependence. This result applies to voids identified at z=0 with effective radius between 1 and 10 h−1 Mpc. Our analytical approximations are flexible enough to give a good description of the resulting volume function; however, this happens for choices of parameter values that are different from those suggested by the spherical evolution assumption. We conclude that analytical models for voids must move away from the spherical approximation in order to be applied successfully to observations, and we discuss some possible ways forwar

Characterizing the diffusional behavior and trafficking pathways of Kv2.1 using single particle tracking in live cells

2013 Spring.Includes bibliographical references.Studying the diffusion pattern of membrane components yields valuable information regarding membrane structure, organization, and dynamics. Single particle tracking serves as an excellent tool to probe these events. We are investigating of the dynamics of the voltage gated potassium channel, Kv2.1. Kv2.1 uniquely localizes to stable, micro-domains on the cell surface where it plays a non-conducting role. The work reported here examines the diffusion pattern of Kv2.1 and determines alternate functional roles of surface clusters by investigating recycling pathways using single particle tracking in live cells. The movement of Kv2.1 on the cell surface is found to be best modeled by the combination of a stationary and non-stationary process, namely a continuous time random walk in a fractal geometry. Kv2.1 surface structures are shown to be specialized platforms involved in trafficking of Kv channels to and from the cell surface in hippocampal neurons and transfected HEK cells. Both Kv2.1 and Kv1.4, a non-clustering membrane protein, are inserted and retrieved from the plasma membrane at the perimeter of Kv2.1 clusters. From the distribution of cluster sizes, using a Fokker-Planck formalism, we find there is no evidence of a feedback mechanism controlling Kv2.1 domain size on the cell surface. Interestingly, the sizes of Kv2.1 clusters are rather governed by fluctuations in the endocytic and exocytic machinery. Lastly, we pinpoint the mechanism responsible for inducing Kv2.1 non-ergodic dynamics: the capture of Kv2.1 into growing clathrin-coated pits via transient binding to pit proteins