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Multi-object tracking driven event detection for evaluation

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AREA '08: Proceedings of the 1st ACM workshop on Analysis and retrieval of events/actions and workflows in video streams

Pages 17 - 24

https://doi.org/10.1145/1463542.1463546

Published: 31 October 2008 Publication History

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Abstract

This paper describes a monocular object tracker, able to detect and track multiple object classes in non-controlled environments. Our tracking framework uses Bayesian per-pixel classification to segment an image into foreground and background objects, based on observations of object appearances and motions in real-time. Furthermore, semantically high level events are automatically extracted from the tracking data for performance evaluation. The reliability of the event detection is demonstrated by applying it to state-of-the-art methods and comparing the results to human annotated ground truth data for multiple public datasets.

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Cited By

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Dragonas JDoulamis AMiaoulis GPlemenos D(2010)Collaborative Foreground Background Object Isolation and TrackingIntelligent Computer Graphics 201010.1007/978-3-642-15690-8_4(67-84)Online publication date: 2010
https://doi.org/10.1007/978-3-642-15690-8_4
Bellotto NSommerlade EBenfold BBibby CReid IRoth DFernandez CVan Gool LGonzalez J(2009)A distributed camera system for multi-resolution surveillance2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC)10.1109/ICDSC.2009.5289413(1-8)Online publication date: Aug-2009
https://doi.org/10.1109/ICDSC.2009.5289413

Index Terms

Multi-object tracking driven event detection for evaluation
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
  2. Computer graphics
    1. Image manipulation
      1. Image processing

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Published In

AREA '08: Proceedings of the 1st ACM workshop on Analysis and retrieval of events/actions and workflows in video streams

October 2008

132 pages

ISBN:9781605583181

DOI:10.1145/1463542

General Chairs:
Anastasios Doulamis
Technical University of Crete, Greece
,
Luc van Gool
Eidgenoessische Technische Hochschule Zuerich, Switzerland
,
Mark Nixon
University of Southampton, United Kingdom
,
Theodora Varvarigou
National Technical University of Athens, Greece
,
Nikolaos Doulamis
National Technical University of Athens, Greece
,
Program Chair:
Manolis Sardis
Aegean University, Greece

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 31 October 2008

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October 31, 2008

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Dragonas JDoulamis AMiaoulis GPlemenos D(2010)Collaborative Foreground Background Object Isolation and TrackingIntelligent Computer Graphics 201010.1007/978-3-642-15690-8_4(67-84)Online publication date: 2010
https://doi.org/10.1007/978-3-642-15690-8_4
Bellotto NSommerlade EBenfold BBibby CReid IRoth DFernandez CVan Gool LGonzalez J(2009)A distributed camera system for multi-resolution surveillance2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC)10.1109/ICDSC.2009.5289413(1-8)Online publication date: Aug-2009
https://doi.org/10.1109/ICDSC.2009.5289413

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Multi-object tracking evaluated on sparse events

Cooperative Object Tracking and Event Detection with Wireless Smart Cameras

Online Empirical Evaluation of Tracking Algorithms

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