DocumentCode :
2995267
Title :
A Multi-sensor Fusion Framework in 3-D
Author :
Jain, Vinesh ; Miller, A.C. ; Mundy, Joseph L.
Author_Institution :
Vision Syst. Inc., Providence, RI, USA
fYear :
2013
fDate :
23-28 June 2013
Firstpage :
314
Lastpage :
319
Abstract :
The majority of existing image fusion techniques operate in the 2-d image domain which perform well for imagery of planar regions but fails in presence of any 3-d relief and provides inaccurate alignment of imagery from different sensors. A framework for multi-sensor image fusion in 3-d is proposed in this paper. The imagery from different sensors, specifically EO and IR, are fused in a common 3-d reference coordinate frame. A dense probabilistic and volumetric 3-d model is reconstructed from each of the sensors. The imagery is registered by aligning the 3-d models as the underlying 3-d structure in the images is the true invariant information. The image intensities are back-projected onto a 3-d model and every discretized location (voxel) of the 3-d model stores an array of intensities from different modalities. This 3-d model is forward-projected to produce a fused image of EO and IR from any viewpoint.
Keywords :
image fusion; image registration; infrared imaging; probability; stereo image processing; 2D image domain; 3D model alignment; 3D multisensor fusion framework; 3D relief; EO image; IR image; back-projection; common 3D reference coordinate frame; dense probabilistic model; discretized location; electrooptical image; forward-projection; image 3D structure; image fusion technique; image intensity; image registration; imagery alignment; infrared image; multisensor image fusion; planar region; true invariant information; volumetric 3D model; voxel; Cameras; Computational modeling; Image reconstruction; Image sensors; Sensor fusion; Solid modeling; 3-d model; multi-sensor fusion; probability; region classification; registration; volumetric models;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition Workshops (CVPRW), 2013 IEEE Conference on
Conference_Location :
Portland, OR
Type :
conf
DOI :
10.1109/CVPRW.2013.54
Filename :
6595893
Link To Document :
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