Speeding Up Object Detection: Fast Resizing in the Integral Image Domain
Department of Computer Sciences, University of Salzburg, Jakob-Haringer-Strasse 2, Salzburg, Austria
9th International Conference on Computer Vision Theory and Applications, volume 1, pages 64-72, 2014
@article{gschwandtner2014speeding,
title={Speeding Up Object Detection},
author={Gschwandtner, Michael and Uhl, Andreas and Unterweger, Andreas},
year={2014}
}
In this paper, we present an approach to resize integral images directly in the integral image domain. For the special case of resizing by a power of two, we propose a highly parallelizable variant of our approach, which is identical to bilinear resizing in the image domain in terms of results, but requires fewer operations per pixel. Furthermore, we modify a parallelized state-of-the-art object detection algorithm which makes use of integral images on multiple scales so that it uses our approach and compare it to the unmodified implementation. We demonstrate that our modification allows for an average speedup of 6.38% on a dual-core processor with hyperthreading and 12.6% on a 64-core multi-processor system, respectively, without impacting the overall detection performance. Moreover, we show that these results can be extended to a whole class of object detection algorithms.
February 1, 2014 by hgpu
