Autonomous behaviors for interactive vehicle animations
Graphical Models - Special issue on SCA 2004
Collaborative diffusion: programming antiobjects
Companion to the 21st ACM SIGPLAN symposium on Object-oriented programming systems, languages, and applications
Excuse me, I need better AI!: employing collaborative diffusion to make game AI child's play
Proceedings of the 2006 ACM SIGGRAPH symposium on Videogames
Simulating crowds with balance dynamics
SIGGRAPH '05 ACM SIGGRAPH 2005 Posters
Group behavior from video: a data-driven approach to crowd simulation
SCA '07 Proceedings of the 2007 ACM SIGGRAPH/Eurographics symposium on Computer animation
Texture Synthesis Based Simulation of Secondary Agents
Motion in Games
Relaxed Steering towards Oriented Region Goals
Motion in Games
Experiment-based modeling, simulation and validation of interactions between virtual walkers
Proceedings of the 2009 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
Pen-to-mime: Pen-based interactive control of a human figure
Computers and Graphics
Encoding user motion preferences in harmonic function path planning
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
From human to humanoid locomotion--an inverse optimal control approach
Autonomous Robots
Tasking networked CCTV cameras and mobile phones to identify and localize multiple people
Proceedings of the 12th ACM international conference on Ubiquitous computing
Long term real trajectory reuse through region goal satisfaction
MIG'11 Proceedings of the 4th international conference on Motion in Games
International Journal of Computer Games Technology
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Pedestrian navigation is a complex function of humandynamics, a desired destination, and the presence of obstacles.People cannot stop and start instantaneously and theirturning abilities are influenced by kinematic and dynamicalconstraints. A realistic model of human walking pathsis an important development for entertainment applicationsand many classes of simulations. We present a novel behavioralmodel of path planning that extends previous modelsthrough its significant use of pedestrian performance statisticsthat were obtained during a suite of experiments. We developan original interpretation of quantitative metrics formeasuring a model's accuracy, and use it to compare ourpath planning approach to a popular contemporary method.Results indicate that this new path planning model better fitsnatural human behavior than previous models.