Embedded surveillance system using background subtraction and Raspberry Pi. Cocorullo, G., Corsonello, P., Frustaci, F., Guachi, L., & Perri, S. In 2015 AEIT International Annual Conference (AEIT), pages 1-5, 10, 2015. IEEE. ![Embedded surveillance system using background subtraction and Raspberry Pi [link]](https://bibbase.org/img/filetypes/link.svg "link")
Website doi abstract bibtex 1 download One of the most challenging problems in computer vision is the ability of understanding video sequences to automatically detect and recognize moving objects. This work presents the development and the inexpensive implementation of an efficient algorithm based on the background subtraction technique adequate for low-cost embedded video surveillance systems. The proposed algorithm exploits the combination of few historical frames with the use of two channels based on the invariant color H and the grayscale level information to achieve high performance and good quality also within the Raspberry-Pi platform. Experimental results show that the implemented algorithm is robust against noises typically occurring in both indoor and outdoor environments.
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abstract = {One of the most challenging problems in computer vision is the ability of understanding video sequences to automatically detect and recognize moving objects. This work presents the development and the inexpensive implementation of an efficient algorithm based on the background subtraction technique adequate for low-cost embedded video surveillance systems. The proposed algorithm exploits the combination of few historical frames with the use of two channels based on the invariant color H and the grayscale level information to achieve high performance and good quality also within the Raspberry-Pi platform. Experimental results show that the implemented algorithm is robust against noises typically occurring in both indoor and outdoor environments.},
bibtype = {inproceedings},
author = {Cocorullo, Giuseppe and Corsonello, Pasquale and Frustaci, Fabio and Guachi, Lorena and Perri, Stefania},
doi = {10.1109/AEIT.2015.7415219},
booktitle = {2015 AEIT International Annual Conference (AEIT)}
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Downloads: 1
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