Saliency Guided Summarization of Molecular Dynamics Simulations

We present a novel method to measure saliency in molecular dynamics simulation data. This saliency measure is based on a multiscale center-surround mechanism, which is fast and efficient to compute. We explore the use of the saliency function to guide the selection of representative and anomalous timesteps for summarization of simulations. To this end, we also introduce a multiscale keyframe selection procedure which automatically provides keyframes representing the simulation at varying levels of coarseness. We compare our saliency guided keyframe approach against other methods, and show that it consistently selects superior keyframes as measured by their predictive power in reconstructing the simulation.