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    Using the Discrete Fourier Transform for Character Motion Blending and Manipulation - a Streamlined Approach
    (The Eurographics Association, 2010) Molnos, Michael R. L.; Laycock, Stephen D.; Day, Andy M.; John Collomosse and Ian Grimstead
    Motion capture data allows natural-looking motion to be bestowed upon simulated characters. Research has sought ways of extending the range of motions it can reproduce. One such method involves blending between captured sequences in the frequency domain. This paper streamlines the approach taken by similar previous work. Higher efficiency is obtained both by shifting computations from runtime to pre-processing and by using a simpler technique, which is also more flexible allowing the method to be used for a greater range of motions. Furthermore, the already-known use of a triangular network defining a continuous blending space is instead presented as an adjustable interface element which is both intuitive and more flexible than applied to earlier work. As before input data may be sparse yet still allows the creation of a continuous spectrum of subtly varying motions, enabling characters to integrate well in their environment. Weighting calculation, blending and Fourier synthesis of realistic-looking motion using five harmonics requires 0.39 ?s per degree of freedom for each frame in the created sequence - a one-off cost incurred only when blending ratios change. This figure can be improved further using the proposed level-of-detail adjustments, which, combined with its small memory footprint, makes the method particularly suitable for the simulation of crowds.
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    Real-Time Traffic Simulation Using Cellular Automata
    (The Eurographics Association, 2010) Applegate, Christopher S.; Laycock, Stephen D.; Day, Andy M.; John Collomosse and Ian Grimstead
    In this paper, we present a method to simulate large-scale traffic networks, at real-time frame-rates. Our novel contributions include a method to automatically generate a road graph from real-life data, and our extension to a discrete traffic model, which we use to simulate traffic, demonstrating continuous vehicle motion between discrete locations. Given Ordnance Survey data, we automatically generate a road graph, identifying roads, junctions, and their connections. We distribute cells at regular intervals throughout the graph, which are used as discrete vehicle locations in our traffic model. Vehicle positions are then interpolated between cells to obtain continuous animation. We test the performance of our model using a 500 x 500m2 area of a real city, and demonstrate that our model can simulate over 600 vehicles at real-time frame-rates (greater than 80 percent network density).