James, Michael

Robson, Stuart

Varley, Nick

English

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2. SfM-MVS methodStraightforward reconstruction of 3D surfaces or DEMs from photosMike R. James1, Stuart Robson2, Nick Varley31Lancaster Environment Centre, Lancaster University, LA1 4YQ, UK, (*m.james@lancs.ac.uk)   2Department of Civil, Environmental & Geomatic Engineering, University College London, London, UK 3Facultad de Ciencias, Universidad de Colima, Bernal Díaz del Castillo # 340, Colima, Col. México1. IntroductionDigital elevation models (DEMs) and 3D surfaces have beengenerated from aerial images for many years, but traditionaltechniques based on conventional photogrammetry usuallyrequire specialist software, expertise, and extensive measurementof control points or features .Using a computer vision approach which combines structure-from-motion1 and multi-view stereo2 (SfM-MVS), 3D models canbe automatically constructed using images from consumercameras with the following advantages:• flexible image capture and free software• significantly reduced control-point requirementsSfM-MVS has been previously used with ground-based images oflava3; here, we explore the error magnitudes involved and use thetechnique to derive DEMs of the Volcán de Colima lava dome.4. Colima datasets• overflights with light aircraft (~30 -160 photos per flight)• images taken using Nikon D90 with 18-105 mm lens• example images shown in box 2, here we reconstruct DEMs for two dates:  26th Dec. 2010 & 27th May, 20115. Colima domet = 0 min. t = 220 min.Example 3D point cloud model (26th Dec. 2010)Georeferencing: use features identified  in web-sourced aerial imagery (and estimated elevation differences)RMS error to control features  ≈1 m(shaded relief DEM shown in box 2)Two models constructed: 26th Dec. 2010 & 27th May, 2011Both independently geo-referenced, then compared by subtraction3. Error assessmentHow accurate is SfM-MVS for surface reconstruction?Two contrasting examples4 are used to assess error magnitudes.Software and Referencesa Reconstruction pipeline: http://blog.neonascent.net/archives/bundler-photogrammetry-packageb Georeferencing: http://www.lancs.ac.uk/staff/jamesm/software/sfm_georef.htm1 Snavely et al  (2006), Photo tourism: Exploring photo collections in 3D, ACM Trans. Graphics, 25, 835-846, doi: 10.1145/1141911.1141964.2 Furukawa & Ponce (2010), Accurate, dense, and robust multiview stereopsis, IEEE Trans. Pattern Anal. Mach. Intell., 32, 1362-1376, doi: 10.1109/TPAMI.2009.161.3 James et al (2011), Lava channel roofing, overflows, breaches and switching: insights from the 2008-2009 eruption of Mt. Etna, Bull. Volcanol.,  doi: 10.1007/s00445-011-0513-9.4 James & Robson (submitted to J.Geophys. Res.) Straightforward reconstruction of 3D surfaces and topography with a camera: Accuracy and geoscience applicationsAcknowledgements: Thanks to H. Tuffen for loan of the Montserrat sample, B. van Wyk de Vries for the Piton de la  Fournaise data• SfM-MVS: 210 photos, viewing distance 0.7 m, scaled by length measurements with steel rule• Benchmark data from Arius3D scanner (25 μm accuracy)• RMS difference ≈300 μm• SfM-MVS: 133 photos taken from micro-light aircraft, viewing distance ~1000 m, model georeferenced by control points• Benchmark DEM from  oblique photogrammetry• RMS difference ≈1.0 mrun the automatic reconstructionadefine scale and georeferencebVolcanic bomb hand sample, ~10 cm acrossPiton de la Fournaise summit craters, ~1.6 km across10-1002-28-86-64-4N50 mimage collection using a consumer camera from different positionsinterpolate point cloud into DEM surface3D coloured point cloud (without scale or orientation)• good accuracy relies on a high quality, convergent image set• relative precision ratio can exceed 1:1000 4i.e. a precision of ±1 mm for each metre of viewing distanceElevation change (m)N50 m areas of deep shadow prevent surface reconstructionindividual areas of loss / gain due to rockfallAA'-1001050 mElevationchange (m)A A'Difference DEMSfM-MVS provides an efficient and effective technique for DEM generation SfM-MVSArius3DCross sections: red = SfM-MVS, black = scanner; inset circular graph gives radial differenceDifference DEM: SfM-MVS vs. benchmark photogrammetry

a Reconstruction pipeline: http://blog.neonascent.net/archives/bundler-photogrammetry-package b Georeferencing: http://www.lancs.ac.uk/staff/jamesm/software/sfm_georef.htm 1 Snavely et al (2006), Photo tourism: Exploring photo collections in 3D,

Accurate, dense, and robust multiview stereopsis,

Lava channel roofing, overflows, breaches and switching: insights from the 2008-2009 eruption of Mt.

Straightforward reconstruction of 3D surfaces or DEMs from photos

http://eprints.lancs.ac.uk/52282/1/James_et_al_SfM_MVS.pdf

Straightforward reconstruction of 3D surfaces or DEMs from photos

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