FPGA Implementation of Support Vector Machines for 3D Object Identification

Authors:
Marta Ruiz-Llata;Mar Yébenes-Calvino
Affiliations:
Departamento de Tecnología Electrónica, Universidad Carlos III de Madrid, Madrid 28911;Departamento de Tecnología Electrónica, Universidad Carlos III de Madrid, Madrid 28911
Venue:
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part I
Year:
2009

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Abstract

In this paper we present a hardware architecture for a Support Vector Machine intended for vision applications to be implemented in a FPGA device. The architecture computes the contribution of each support vector in parallel without performing multiplications by using a CORDIC algorithm and a hardware-friendly kernel function. Additionally input images are not preprocessed for feature extraction as each image is treated as a point in a high dimensional space.