Multiple video object tracking using variational inference

Kangin, Dmitry and Kolev, Denis Georgiev and Markarian, Garegin (2015) Multiple video object tracking using variational inference. In: 2015 Sensor Data Fusion: Trends, Solutions, Applications (SDF 2015). IEEE, DEU, pp. 47-52. ISBN 9781467371766

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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.

Item Type:
Contribution in Book/Report/Proceedings
ID Code:
78072
Deposited By:
Deposited On:
14 Jun 2016 08:32
Refereed?:
Yes
Published?:
Published
Last Modified:
27 Sep 2020 06:26