Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
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TY - GEN
T1 - RTSDE
T2 - 2014 IEEE Symposium Series on Computational Intelligence
AU - Angelov, Plamen
AU - Wilding, Ashley
N1 - Date of Acceptance 06/09/2014
PY - 2014/12/9
Y1 - 2014/12/9
N2 - 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 signalprocessors, allowing for high definition video to be processed for novelty detection in real-time.
AB - 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 signalprocessors, allowing for high definition video to be processed for novelty detection in real-time.
KW - Kernel Density Estimation
KW - recursive density estimation (RDE)
KW - background subtraction
KW - novelty detection
KW - video analytics
KW - embedded systems
KW - Digital Signal Processors
KW - integer-only arithmetic
KW - no FLOPs
U2 - 10.1109/EALS.2014.7009507
DO - 10.1109/EALS.2014.7009507
M3 - Conference contribution/Paper
SN - 9781479944958
SP - 81
EP - 86
BT - 2014 IEEE Symposium on Evolving and Autonomous Learning Systems (EALS)
PB - IEEE
CY - Orlando, FL, USA
Y2 - 9 December 2014 through 12 December 2014
ER -