%0 Book Section %B Computer Vision – ECCV 2010Computer Vision – ECCV 2010 %D 2010 %T Aligning Spatio-Temporal Signals on a Special Manifold %A Ruonan Li %A Chellapa, Rama %E Daniilidis,Kostas %E Maragos,Petros %E Paragios,Nikos %X We investigate the spatio-temporal alignment of videos or features/signals extracted from them. Specifically, we formally define an alignment manifold and formulate the alignment problem as an optimization procedure on this non-linear space by exploiting its intrinsic geometry. We focus our attention on semantically meaningful videos or signals, e.g., those describing or capturing human motion or activities, and propose a new formalism for temporal alignment accounting for executing rate variations among realizations of the same video event. By construction, we address this static and deterministic alignment task in a dynamic and stochastic manner: we regard the search for optimal alignment parameters as a recursive state estimation problem for a particular dynamic system evolving on the alignment manifold. Consequently, a Sequential Importance Sampling iteration on the alignment manifold is designed for effective and efficient alignment. We demonstrate the performance on several types of input data that arise in vision problems. %B Computer Vision – ECCV 2010Computer Vision – ECCV 2010 %S Lecture Notes in Computer Science %I Springer Berlin / Heidelberg %V 6315 %P 547 - 560 %8 2010/// %@ 978-3-642-15554-3 %G eng %U http://dx.doi.org/10.1007/978-3-642-15555-0_40