Advertisement
Published in:
2010 | OriginalPaper | Chapter
A Salient Region Detector for GPU Using a Cellular Automata Architecture
Authors : David Huw Jones, Adam Powell, Christos-Savvas Bouganis, Peter Y. K. Cheung
Published in: Neural Information Processing. Models and Applications
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
The human visual cortex performs salient region detection, a process critical to the rapid understanding of a scene. This is performed on large arrays of locally interacting neurons that are slow to simulate sequentially. In this paper we describe and evaluate a novel, bio-inspired, cellular automata (CA) architecture for the determination of the salient regions within a scene. This parallel processing architecture is appropriate for implementation on a graphics processing unit (GPU). We compare the performance of this algorithm against that of CPU implemented salient region detectors. The CA algorithm is less subject to variation due to changing scale, viewpoint and illumination conditions. Also due to its GPU implementation, this algorithm is able to detect salient regions faster than the CPU implemented algorithms.