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Multiple video object tracking using variational inference

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Published
Publication date6/10/2015
Host publication2015 Sensor Data Fusion: Trends, Solutions, Applications (SDF 2015)
PublisherIEEE
Pages47-52
Number of pages6
ISBN (print)9781467371766
<mark>Original language</mark>English
EventWorkshop on Sensor Data Fusion: Trends, Solutions, Applications - Bonn, Germany
Duration: 6/10/20159/10/2015

Conference

ConferenceWorkshop on Sensor Data Fusion: Trends, Solutions, Applications
Country/TerritoryGermany
CityBonn
Period6/10/159/10/15

Conference

ConferenceWorkshop on Sensor Data Fusion: Trends, Solutions, Applications
Country/TerritoryGermany
CityBonn
Period6/10/159/10/15

Abstract

In this article a Bayesian filter approximation is proposed for simultaneous multiple target detection and tracking and then applied for object detection on video from moving camera. The inference uses the evidence lower bound optimisation for Gaussian mixtures. The proposed filter is capable of real time data processing and may be used as a basis for data fusion. The method we propose was tested on the video with dynamic background,where the velocity with respect to the background is used to discriminate the objects. The framework does not depend on the feature space, that means that different feature spaces can be unrestrictedly used while preserving the structure of the filter.