Authors:
Michael Gschwandtner
;
Andreas Uhl
and
Andreas Unterweger
Affiliation:
University of Salzburg, Austria
Keyword(s):
Integral Image, Resizing, Object Detection, Performance.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Image Formation and Preprocessing
;
Image Generation Pipeline: Algorithms and Techniques
Abstract:
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
hyper-threading 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.