Abstract
Till today face detection is a burning topic for the researchers. In the areas like digital media, intelligent user interface, intelligent visual surveillance and interactive games. Various noises and blurring effects face images captured in real time. Single board computer for efficient face detection system is introduced in this paper which works well in the presence of Gaussian Noise, Salt & Pepper Noise, Motion Blur and Gaussian Blur. Raspberry Pi based single-board computer is used for the experiments, because it consumes less power and is available at an affordable price. The developed system is tested by introducing varying degree of noises and blurring effects on standard public face databases: GRIMACE, JAFEE, INDIAN FACE, CALTECH, FACE 95, FEI – 1, FEI – 2. In the absence of noise and blurring effects also the system is tested using standard public face databases: GRIMACE, JAFEE, INDIAN FACE, CALTECH, FACE 95, FEI – 1, FEI – 2, HEAD POSE IMAGE, SUBJECT, and FGNET. The key advantage of the proposed system is excellent face detection rates in the presence of noises, blurring effects and also in the presence of varying facial expressions and across age progressions. Python scripts are developed for the system, resulted are shared on request.
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Fernandes, S.L., Bala, J.G. (2015). Low Power Affordable and Efficient Face Detection in the Presence of Various Noises and Blurring Effects on a Single-Board Computer. In: Satapathy, S., Govardhan, A., Raju, K., Mandal, J. (eds) Emerging ICT for Bridging the Future - Proceedings of the 49th Annual Convention of the Computer Society of India (CSI) Volume 1. Advances in Intelligent Systems and Computing, vol 337. Springer, Cham. https://doi.org/10.1007/978-3-319-13728-5_13
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DOI: https://doi.org/10.1007/978-3-319-13728-5_13
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