Abstract
We investigate the advantages of a stereo, multi-spectral acquisition system for material classification 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 classification 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 classification using acquired images compares favourably to using a standard camera.
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Bradbury, G.: Material Classification in Outdoor Scenes. MSc Computer Graphics, Vision and Imaging. University College London (2010)
Breiman, L.: Random Forests. Machine Lerarning 45(1), 29 (2001)
Brown, M., Susstrunk, S.: Multi-spectral SIFT for Scene Category Recognition. In: Computer Vision and Pattern Recognition (CVPR 2011), pp. 177–184 (2011)
Fyffe, G.: Single-Shot Photometric Stereo by Spectral Multiplexing. Proceedings ACM SIGGRAPH Asia Sketches, 2–7 (2010)
Geiger, A., Roser, M., Urtasun, R.: Efficient large-scale stereo matching. In: Kimmel, R., Klette, R., Sugimoto, A. (eds.) ACCV 2010, Part I. LNCS, vol. 6492, pp. 25–38. Springer, Heidelberg (2011)
Habel, R., Kudenov, M., Wimmer, M.: Practical spectral photography. Computer Graphics Forum (Proceedings EUROGRAPHICS 2012) 31(2), 449–458 (2012)
Hernandez-Stefanoni, L., Ponce-Hernandez, R.: Mapping the Spatial Distribution of Plant Diversity Indices in a Tropical Forest Using Multi-Spectral Satellite Image Classification and Field Measurements. Biodiversity and Conservation 13(14), 2599–2621 (2004)
Kim, M., Harvey, T., Kittle, D., Rushmeier, H., Dorsey, J., Prum, R., Brady, D.: 3D Imaging Spectroscopy for Measuring Hyperspectral Patterns on Solid Objects. ACM Trans. on Graphics (Proc. SIGGRAPH) 31(4), 38:1–38:11 (2012)
Palmer, A., Tanser, F.: Vegetation Mapping of the Great Fish River Basin, South Africa: Integrating Spatial and Multi-Spectral Remote Sensing Techniques, pp. 197–204 (2000)
Qi, Z.: Extraction of Spectral Reflectance Images From Multi-Spectral Images by the HIS Transformation Model. International Journal of Remote Sensing 17, 3467–3475 (1996)
Shrestha, R., Hardeberg, J.Y., Mansouri, A.: One-Shot Multispectral Color Imaging with a Stereo Camera. In: Digital Photography VII. Proceedings of the SPIE, vol. 7876, pp. 787609–787609–11(2011)
Subr, K., Bradbury, G., Kautz, J.: Binocular-Stereo Photography Under a Light-Budget. In: Proceedings of CVMP 2012, pp. 1–10 (2012)
Susstrunk, S., Firmenich, D., Brown, M.: Multispectral Interest Points for RGB-NIR Image Registration. In: International Conference on Image Processing (ICIP 2011), pp. 4–7 (2011)
Tsuchida, M., Yano, K., Tanaka, H.T.: Development of a High-Definition and Multispectral Image Capturing System for Digital Archiving of Early Modern Tapestries of Kyoto Gion Festival. In: 2010 20th International Conference on Pattern Recognition, pp. 2828–2831 (August 2010)
Wolf, D., Howard, A., Sukhatme, G.: Towards Geometric 3D Mapping of Outdoor Environments Using Mobile Robots. In: 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1507–1512 (2005)
Yu, Q., Gong, P., Clinton, N., Biging, G., Kelly, M., Schirokauer, D.: Object-based Detailed Vegetation Classification with Airborne High Spatial Resolution Remote Sensing Imagery. Photogrammetric Engineering and Remote sensing 72(7), 799–811 (2006)
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Bradbury, G., Mitchell, K., Weyrich, T. (2013). Multi-spectral Material Classification in Landscape Scenes Using Commodity Hardware. In: Wilson, R., Hancock, E., Bors, A., Smith, W. (eds) Computer Analysis of Images and Patterns. CAIP 2013. Lecture Notes in Computer Science, vol 8048. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40246-3_26
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DOI: https://doi.org/10.1007/978-3-642-40246-3_26
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