LCrowdV: Generating Labeled Videos for Simulation-based Crowd Behavior Learning

We present a novel procedural framework to generate an arbitrary number of labeled crowd videos (LCrowdV). The resulting crowd video datasets are used to design accurate algorithms or training models for crowded scene understanding. Our overall approach is composed of two components: a procedural simulation framework for generating crowd movements and behaviors, and a procedural rendering framework to generate different videos or images. Each video or image is automatically labeled based on the environment, number of pedestrians, density, behavior, flow, lighting conditions, viewpoint, noise, etc. Furthermore, we can increase the realism by combining synthetically-generated behaviors with real-world background videos. We demonstrate the benefits of LCrowdV over prior lableled crowd datasets by improving the accuracy of pedestrian detection and crowd behavior classification algorithms. LCrowdV would be released on the WWW

Small eta-N scattering lengths favour eta-d and eta-alpha states

Unstable states of the eta meson and the 3He nucleus predicted using the time delay method were found to be in agreement with a recent claim of eta-mesic 3He states made by the TAPS collaboration. Here, we extend this method to a speculative study of the unstable states occurring in the eta-d and eta-4He elastic scattering. The T-matrix for eta-4He scattering is evaluated within the Finite Rank Approximation (FRA) of few body equations. For the evaluation of time delay in the eta-d case, we use a parameterization of an existing Faddeev calculation and compare the results with those obtained from FRA. With an eta-N scattering length, $a_{\eta N} = (0.42, 0.34)$ fm, we find an eta-d unstable bound state around -16 MeV, within the Faddeev calculation. A similar state within the FRA is found for a low value of $a_{\eta N}$, namely, $a_{\eta N} = (0.28, 0.19)$ fm. The existence of an eta-4He unstable bound state close to threshold is hinted by $a_{\eta N} = (0.28, 0.19)$ fm, but is ruled out by large scattering lengths.Comment: 21 pages, LaTex, 7 Figure

Virtual reality crowd simulation: effects of agent density on user experience and behaviour

Agent-based crowd simulations are used for modelling building and space usage, allowing designers to explore hypothetical real-world scenarios, including extraordinary events such as evacuations. Existing work which engages virtual reality (VR) as a platform for crowd simulations has been primarily focussed on the validation of simulation models through observation; the use of interactions such as gaze to enhance a sense of immersion; or studies of proxemics. In this work, we extend previous studies of proxemics and examine the effects of varying crowd density on user experience and behaviour. We have created a simulation in which participants walk freely and perform a routine manual task, whilst interacting with agents controlled by a typical social force simulation model. We examine and report the effects of crowd density on both affective state and behaviour. Our results show a significant increase in negative affect with density, measured using a self-report scale. We further show significant differences in some aspects of user behaviours, using video analysis, and discuss how our results relate to VR simulation design for mixed human–agent scenarios