Fast stochastic optimization for articulated structure tracking
Recently, an optimization approach for fast visual tracking of articulated structures based on stochastic meta-descent (SMD)  has been presented. SMD is a gradient descent with local step size adaptation that combines rapid convergence with excellent scalability. Stochastic sampling helps to avoid local minima in the optimization process. We have extended the SMD algorithm with new features for fast and accurate tracking by adapting the different step sizes between as well as within video...[Show more]
|Collections||ANU Research Publications|
|Source:||Image and Vision Computing|
|01_Bray_Fast_stochastic_optimization_2007.pdf||1.43 MB||Adobe PDF||Request a copy|
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