Application of Symmetrical SURF with Global Context in Vehicle Detection

doi:10.3969/j.issn.1006-2475.2015.01.016

Abstract

Abstract: SURF（SpeedUp Robust Features） is a robust and fast descriptor for many applications, but neither can it detect symmetrical matches, nor can it consider global context. This paper combines symmetrical SURF with global context. It enables SURF to detect symmetrical matches through mirroring transformation and reduces mismatches when local descriptors are similar. The proposed algorithm is used in vehilce detection. The experiments show that symmetrical SURF with global context improves the accuracy of feature matches and vehicle detection.
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Key words: symmetrical SURF, global context, vehicle detection

CLC Number:

TP391

XIONG Yan-cheng, SUN Han. Application of Symmetrical SURF with Global Context in Vehicle Detection[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2015.01.016.

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