Anzeige
Erschienen in:
2010 | OriginalPaper | Buchkapitel
Egocentric Visual Event Classification with Location-Based Priors
verfasst von : Sudeep Sundaram, Walterio W. Mayol-Cuevas
Erschienen in: Advances in Visual Computing
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
We present a method for visual classification of actions and events captured from an egocentric point of view. The method tackles the challenge of a moving camera by creating deformable graph models for classification of actions. Action models are learned from low resolution, roughly stabilized difference images acquired using a single monocular camera. In parallel, raw images from the camera are used to estimate the user’s location using a visual Simultaneous Localization and Mapping (SLAM) system. Action-location priors, learned using a labeled set of locations, further aid action classification and bring events into context. We present results on a dataset collected within a cluttered environment, consisting of routine manipulations performed on objects without tags.