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A Fast Recursive Approach to Autonomous Detection, Identification and Tracking of Multiple Objects in Video Streams under Uncertainties

Research output: Contribution in Book/Report/ProceedingsPaper

Published

Publication date07/2010
Host publicationInformation Processing and Management of Uncertainty in Knowledge-Based Systems. Applications : 13th International Conference, IPMU 2010, Dortmund, Germany, June 28–July 2, 2010. Proceedings, Part II
EditorsEyke Hüllermeier, Rudolf Kruse, Frank Hoffmann
Place of publicationBerlin
PublisherSpringer
Pages30-43
Number of pages14
ISBN (Print)978-3-642-14057-0
Original languageEnglish

Conference

ConferenceInternational Conference on Information Processing and Uncertainty Management, IPMU 2010
CityDortmund, Germany
Period28/06/102/07/10

Publication series

NameCommunications in Computer and Information Science
PublisherSpringer
Volume81
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

ConferenceInternational Conference on Information Processing and Uncertainty Management, IPMU 2010
CityDortmund, Germany
Period28/06/102/07/10

Abstract

Real-time processing the information coming form video, infra-red or electro-optical sources is a challenging task due the uncertainties such as noise and clutter, but also due to the large dimensionalities of the problem and the demand for fast and efficient algorithms. This paper details an approach for automatic detection, single and multiple objects identification and tracking in video streams with applications to surveillance, security and autonomous systems. It is based on a method that provides recursive density estimation (RDE) using a Cauchy type of kernel. The main advantage of the RDE approach as compared to other traditional methods (e.g. KDE) is the low computational and memory storage cost since it works on a frame-by-frame basis; the lack of thresholds, and applicability to multiple objects identification and tracking. A robust to noise and clutter technique based on spatial density is also proposed to autonomously identify the targets location in the frame.