Egocentric visual event classification with location-based priors

Sudeep Sundaram, Walterio Mayol-Cuevas

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

7 Citations (Scopus)
284 Downloads (Pure)

Abstract

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 labelled 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.
Translated title of the contributionEgocentric Visual Event Classification with Location-Based Priors
Original languageEnglish
Title of host publicationInternational Symposium on Visual Computing
PublisherSpringer
Pages596-605
Number of pages10
ISBN (Electronic)9783642172748
ISBN (Print)9783642172731
DOIs
Publication statusPublished - 10 Nov 2010
Event6th International Symposium on Visual Computing - Las Vegas, United States
Duration: 10 Nov 2010 → …

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Berlin Heidelberg
Volume6454
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th International Symposium on Visual Computing
CountryUnited States
CityLas Vegas
Period10/11/10 → …

Bibliographical note

Other page information: -
Conference Proceedings/Title of Journal: International Symposium on Visual Computing
Other identifier: 2001256
Rose publication type: Conference contribution

Additional information: Author's own post-print version of a paper published by Springer in volume 6454 of the Lecture Notes in Computer Science series. The original publication is available at www.springerlink.com

Sponsorship: The authors are deeply grateful to the British Council for the PhD studentship granted to SS,
and to the EUFP7 COGNITO project for partially funding WMC

ISSN: 0302-9743 (print), 1611-3349 (online)

Keywords

  • event recognition
  • SLAM
  • wearable computing
  • simultaneous localization and mapping

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