Post on 05-Jul-2015
description
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Buildings Recognition and Camera Localization Using Image Texture
Description SULEIMAN Wassim1, JOLIVEAU Thierry1,
FAVIER Eric2
1ISTHME-ISIG CNRS/UMR EVS, Université Jean Monnet - Saint-Etienne. 2DIPI EA 3719 École Nationale d'Ingénieurs de Saint-Etienne
wassim.suleiman@univ-st-etienne.fr thierry.joliveau@univ-st-etienne.fr
eric.favier@enise.fr
25th International Cartographic Conference (Sageo) – 8 july 2011 – Palais de congrès Paris
Objective
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Find a building in an image
SIG 3D3D GIS
Locate the camera that took the image by using the location of the building
Methodology
Enhancing the GIS database with information which can describe the building
unique information quantifiable information
■ The texture signature
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Texture signature
How to isolate the building facade in the image?
Manual method (long)
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Sourimant 2009
Automatic method : (3D SIG model/2D image) registration (simple building)
Work plan
1. GIS database enhancement with building texture information
2. Facade recognition3. Camera geolocation 4. Possible applications5. Limits
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Work plan
q Enhancing GIS databases with building texture information
q Facade recognitionq Camera Geolocation q Possible Applicationsq Limits
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Enhancing GIS databases with building texture information
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Texture analyses(SIFT)
Finding the interest points with their local descriptor
Enhancing GIS databases with building texture information
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Finding the (x,y,z) of the interest points
Homography constraints
3D GIS model
Enhancing GIS databases with building texture information
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The texture descriptor :
list of interest points with their local descriptor and their 3D position
Work plan
q Enhancing GIS databases with building texture information
q Facade recognitionq Camera Geolocation q Possible Applicationsq Limits
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Facade recognition
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False matching because of the locality of the descriptor
Facade recognition
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Eliminate the false matching using the homography constraints
Select the best matching score between the current image and the stored descriptor in the databases
Facade recognition
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The facade in the 3D GIS
Work plan
q Enhancing the GIS database with building texture information
q Facade recognition
q Camera geolocation q Possible applicationsq Limits
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Camera Geolocation
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Association of the interest points with the 3D position of the matched points in the GIS databases
Camera geolocation
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4 points non-collinear (Yang & al. 2009)
Real position Measured position
Camera Geolocation
Error for distance (20-100)m and angle (0-30°) camera direction and facade normal :■ Position : 1 - 3 m■ Orientation : 5 - 10°
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Error because the texture description is not an affine function 18
Real positionMeasured position
4 points non-coplanaires SOFTPOSIT (David et al. 2004)
Camera Geolocation
Work plan
q Enhancing the GIS database with building texture information
q Facade recognitionq Camera geolocation
q Possible applicationsq Limits
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Possible Applications
Management of photos taken in urban areas
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Link
GIS
Possible Applications Navigation systems support in an urban
environment
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Satellites visibility Multipath
Possible applications
Initial phase in the (2D/3D) registration
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Sourimant 2009
Work plan
q Enhancing the GIS database with building texture information
q Facade recognitionq Camera geolocation q Possible applications
q Limits
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Limits Angle between camera direction and facade
normal has to be less than 30°
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Limits
Distance between camera and facade has to be less than 200 m
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Limits
Identical facades :
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Limits
Glass facade which reflects the sky and other buildings
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Thank youFor your attention
Suleiman wassimwassim.suleiman@univ-st-etienne.fr