Estimating adaptive coefficients of evolving GMMs for online video segmentation

Kaloskampis, Ioannis ORCID: https://orcid.org/0000-0002-4450-4935 and Hicks, Yulia Alexandrovna ORCID: https://orcid.org/0000-0002-7179-4587 2014. Estimating adaptive coefficients of evolving GMMs for online video segmentation. Presented at: 6th International Symposium on Communications, Control and Signal Processing, Athens, Greece, 21-23 May 2014. 2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP). Picastaway, NY: IEEE, pp. 513-516. 10.1109/ISCCSP.2014.6877925

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Abstract

A new, online, evolving video segmentation algorithm is presented in this paper. The proposed method segments each video frame using an evolving Gaussian mixture model (GMM) whose adaptive coefficient is automatically adjusted to cater for abrupt changes between consecutive frames. The proposed method is tested against another algorithm, which keeps the adaptive coefficient constant. The comparison shows the advantage of altering the value of the adaptive coefficient according to change in the scene.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Engineering
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software
Publisher:	IEEE
Last Modified:	27 Oct 2022 09:10
URI:	https://orca.cardiff.ac.uk/id/eprint/64641

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