In this paper, we consider the problem of face detection under pose variations. Unlike other contributions, a focus of this work resides within efficient implementation utilizing the computational powers of modern graphics cards. The proposed system consists of a parallelized implementation of convolutional neural networks (CNNs) with a special emphasize on also parallelizing the detection process. Experimental validation in a smart conference room with 4 active ceiling-mounted cameras shows a dramatic speed-gain under real-life conditions. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Nasse, F., Thurau, C., & Fink, G. A. (2009). Face detection using gpu-based convolutional neural networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5702 LNCS, pp. 83–90). https://doi.org/10.1007/978-3-642-03767-2_10
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