Facial Recognition Using Neural Networks over GPGPU

Authors

  • Juan Pablo Balarini
  • Sergio Nesmachnow
  • Martín Rodríguez

DOI:

https://doi.org/10.19153/cleiej.15.3.6

Abstract

This article introduces a parallel neural network approach implemented over Graphic Processing Units (GPU) to solve a facial recognition problem, which consists in deciding where the face of a person in a certain image is pointing. The proposed method uses the parallel capabilities of GPU in order to train and evaluate a neural network used to solve the abovementioned problem.

The experimental evaluation demonstrates that a significant reduction on computing times can be obtained allowing solving large instances in reasonable time. Speedup greater than 8 is achieved when contrasted with a sequential implementation and classification rate superior to 85 % is also obtained.

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Published

2012-12-01

Issue

Vol. 15 No. 3 (2012): Selected papers from HPCLatAM2012

Section

Articles

License

CLEIej is supported by its home institution, CLEI, and by the contribution of the Latin American and international researchers community, and it does not apply any author charges whatsoever for submitting and publishing. Since its creation in 1998, all contents are made publicly accesibly. The current license being applied is a (CC)-BY license (effective October 2015; between 2011 and 2015 a (CC)-BY-NC license was used).