Fast Vision-Based Object Recognition Using Combined Integral Map
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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. |
| Author:
| Tam Phuong Cao, Guang Deng;Darrell Elton |
| Year: | |
| Source: | Computer Vision Systems |
| Volume-OnPage: | 445-454 |
| Keyword: | |
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