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Multi-spectral SIFT for Scene Category Recognition

8 years 2 months ago
Multi-spectral SIFT for Scene Category Recognition
We use a simple modification to a conventional SLR camera to capture images of several hundred scenes in colour (RGB) and near-infrared (NIR). We show that the addition of near-infrared information leads to significantly improved performance in a scene-recognition task, and that the improvements are greater still when an appropriate 4-dimensional colour representation is used. In particular we propose MSIFT – a multispectral SIFT descriptor that, when combined with a kernel based classifier, exceeds the performance of state-of-the-art scene recognition techniques (e.g., GIST) and their multispectral extensions. We extensively test our algorithms using a new dataset of several hundred RGB-NIR scene images, as well as benchmarking against Torralba’s scene categorization dataset.
Matthew Brown, Sabine Susstrunk
Added 05 Apr 2011
Updated 29 Apr 2011
Type Journal
Year 2011
Where CVPR
Authors Matthew Brown, Sabine Susstrunk
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