room EM 3.06, Thursday 8th March, 1:15 pm
Wasit Limprasert: Tracking multiple human subjects within a camera network
Abstract: We present an approach to tracking multiple human subjects within a camera network. A particle filter framework is used in which we combine foreground-background subtraction with a novel approach to texture learning and likelihood computation based on an ellipsoid model. As there are inevitable problems with multiple subjects due to occlusion and crossing, we include a robust method to suppress distraction between subjects. To achieve real-time performance, we have also developed our code on a graphics processing unit to achieve a 10-fold reduction in processing time with an approximate frame rate of 10 frame per second.
Qi, Lin: Measuring Perceived Gloss of Rough Surfaces
We have studied how perceived gloss varies with the change of both mesoscale and microscale roughness on 3D surface textures. The mesoscale roughness was changed by varying the roll-off factor (β) of 1/fβ fractal noise surfaces. The microscale roughness was changed by varying the microscale roughness parameter α in the microfacet reflection model. An HDR real-world environment map was used to provide complex illumination and a physically-based path tracer was used for rendering the stimuli. Each simulated surface was rotated about its vertical axis to generate an animated stimulus. Eight observers took part in a 2AFC experiment, and the results were tested against conjoint measurement models. We found that the perceived gloss changes non-monotonically with β (an asymmetric bell curve), and monotonically with α. Although both β and α significantly affect perceived gloss, the additive model is inadequate to describe their interactive and nonlinear influence, which is at variance with previous results.
Ritter, Christopher: Can virtual characters learn to care? How to increase an agent's ability to empathise!
My PhD is motivated by the attempt to find a computational model for intelligent and emotional characters that can learn to be more empathic towards other agents (a dynamic adaptation process). I intend to achieve this goal by including models of emotional (self-)awareness - affective empathy - and cognitive empathy into the agent's reasoning. In order to generate a more natural looking model of the simulated learning process, I started by looking into how real people can learn/be taught to be more empathic. I will present a WIP showcase I am creating based on findings in the area of conflict resolution. I will use the showcase to create a model for the learning process as observed in this particular situation. A later implementation of the showcase will be used to evaluate the model. No explicit implementation model is presented yet!
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