Disney Research


We investigate the advantages of a stereo, multi-spectral acquisition system for material classi cation in ground-level landscape images. Our novel system allows us to acquire high-resolution, multi- spectral stereo pairs using commodity photographic equipment. Given additional spectral information we obtain better classi cation of vegetation classes than the standard RGB case. We test the system in two modes: splitting the visible spectrum into six bands and extending the recorded spectrum to near infra-red. Our six-band design is more practical than standard multi-spectral techniques and foliage classi cation using acquired images compares favourably to using a standard camera.

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