RTSDE:recursive total-sum-distances-based density estimation approach and its application for autonomous real-time video analytics

Angelov, Plamen and Wilding, Ashley (2014) RTSDE:recursive total-sum-distances-based density estimation approach and its application for autonomous real-time video analytics. In: 2014 IEEE Symposium on Evolving and Autonomous Learning Systems (EALS). IEEE, USA, pp. 81-86. ISBN 9781479944958

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Abstract

In this paper, we propose a new approach to data density estimation based on the total sum of distances from a data point, and the recently introduced Recursive Density Estimation technique. It is suitable for autonomous real-time video analytics problems, and has been specifically designed to be executed very fast; it uses integer-only arithmetic with no divisions and no floating point numbers (no FLOPs), making it particularly useful in situations where a hardware floating point unit may not be available, such as on embedded hardware and digital signal processors, allowing for high definition video to be processed for novelty detection in real-time.

Item Type:
Contribution in Book/Report/Proceedings
Additional Information:
Date of Acceptance 06/09/2014
Subjects:
ID Code:
72785
Deposited By:
Deposited On:
30 Jan 2015 11:32
Refereed?:
Yes
Published?:
Published
Last Modified:
01 Jan 2020 05:49