Fast Vision-Based Object Recognition Using Combined Integral Map

Authors:
Tam Phuong Cao;Guang Deng;Darrell Elton
Affiliations:
Department of Electronic Engineering, La Trobe University, Vic, Australia 3086;Department of Electronic Engineering, La Trobe University, Vic, Australia 3086;Department of Electronic Engineering, La Trobe University, Vic, Australia 3086
Venue:
ICVS '09 Proceedings of the 7th International Conference on Computer Vision Systems: Computer Vision Systems
Year:
2009

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Abstract

Integral images or integral map (IMap) is one of the major techniques that has been used to improve the speed of computer vision systems. It has been used to compute Haar features and histograms of oriented gradient features. Some modifications have been proposed to the original IMap algorithm, but most proposed systems use IMap as it was first introduced. The IMap may be further improved by reducing its computational cost in multi-dementional feature domain. In this paper, a combined integral map (CIMap) technique is proposed to efficiently build and use multiple IMaps using a single concatenated map. Implementations show that using CIMap can signifficantly improve system speed while maintaining the accuracy.