Parallel Implementation of Good Feature Extraction for Tracking on the Cell Processor with OpenCV Interface

Authors:
Hiroki Sugano;Ryusuke Miyamoto
Affiliations:
-;-
Venue:
IIH-MSP '09 Proceedings of the 2009 Fifth International Conference on Intelligent Information Hiding and Multimedia Signal Processing
Year:
2009

Citing 0
Cited 2

Highly optimized implementation of OpenCV for the Cell Broadband Engine

Computer Vision and Image Understanding
Parallel implementation of Gray Level Co-occurrence Matrices and Haralick texture features on cell architecture

The Journal of Supercomputing

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Abstract

One of the most widely used schemes to extract feature points suitable for tracking in computer vision is ``Good Features to Track''. In this paper, we propose parallel implementation of the good feature extraction scheme optimized for the Cell processor, which is one of the latest high performance embedded processors. By utilizing the computational power of Cell suitable for image processing, we achieve high-speed computation of the operation. Experimental results show that our implementation with 6 SPEs can compute the feature point extraction in 1.4 ms when the input image size is $640\times 480$ pixels. This is about 5 times faster than the computation on Intel(R) Core(TM)2 Duo CPU E6850 @ 3.00GHz with Intel Integrated Performance Primitives. This work is part of the CVCell project which is a software library compatible with OpenCV library optimized for the Cell processor.