A novel background subtraction scheme for in-camera acceleration in thermal imagery

 
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2016 (EN)

A novel background subtraction scheme for in-camera acceleration in thermal imagery (EN)

Νικητακης Αντωνιος (EL)
Μακαντασης Κωνσταντινος (EL)
Παπαευσταθιου Ιωαννης (EL)
Doulamis, Anastasios (EN)
Makantasis Konstantinos (EN)
Nikitakis Antonios (EN)
Papaefstathiou Ioannis (EN)

Πολυτεχνείο Κρήτης (EL)
Technical University of Crete (EN)

Real-time segmentation of moving regions in image sequences is a very important task in numerous surveillance and monitoring applications. A common approach for such tasks is the background subtraction which tries to extract regions of interest from the image background for further processing or action; as a result its accuracy as well as its real-time performance is of great significance. In this work we utilize a novel scheme, designed and optimized for FPGA-based implementations, which models the intensities of each pixel as a mixture of Gaussian components; following a Bayesian approach, our method automatically estimates the number of Gaussian components as well as their parameters. Our novel system is based on an efficient and highly accurate on-line updating mechanism, which permits our system to be automatically adapted to dynamically changing operation conditions, while it avoids over/under fitting. We also present two reference implementations of our Background Subtraction Parallel System (BSPS) in Reconfigurable Hardware achieving both high performance as well as low power consumption; the presented FPGA-based systems significantly outperform a multi-core ARM and two multi-core low power Intel CPUs in terms of energy consumed per processed pixel as well as frames per second. Moreover, our low-cost, low-power devices allow for the implementation, for the first time, of a highly distributed surveillance system which will alleviate the main problems of the existing centralized approaches. (EN)

full paper
conferenceItem

Surveillance (EN)
Background subtraction (EN)
FPGA (EN)
Low power (EN)
Gaussian mixture model (EN)
Monitoring (EN)


19th Design, Automation and Test in Europe Conference and Exhibition (EL)

English

2016


Institute of Electrical and Electronics Engineers (EN)




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