DocumentCode :
2352695
Title :
Video to reference image alignment in the presence of sparse features and appearance change
Author :
Hirvonen, D. ; Matei, B. ; Wildes, R. ; Hsu, S.
Author_Institution :
Vision Technol., Sarnoff Corp., Princeton, NJ, USA
Volume :
2
fYear :
2001
fDate :
2001
Abstract :
A robust, multi-frame, progressive refinement framework for registering narrow field of view video to reference imagery is presented. A major strength of the approach is its effectiveness in the presence of dissimilar video and reference image appearance. Normalized oriented energy image pyramids are employed to enable alignment of images with global visual dissimilarities, yet local feature commonality. Local matching is then applied coarse-to-fine, along four dimensions: spatial frequency, local support, search range, and model order (a robust parametric model fit is used to reject outliers at each iteration). Globally optimal multi-frame alignment is obtained with respect to several constraints: frame-to-reference local matches, recovered frame-to-frame motion, and optional a priori estimates of sensor pose. The framework is described in detail and applied to two examples: aerial video to geographic reference image alignment (georegistration) and retinal slit lamp video to fundus image alignment.
Keywords :
image matching; image registration; search problems; video signal processing; aerial video; appearance change; dissimilar video; frame-to-reference; fundus image alignment; geographic reference image alignment; georegistration; global visual dissimilarities; globally optimal multi-frame alignment; image alignment; local feature commonality; local matches; local matching; local support; model order; narrow field of view video; normalized oriented energy image pyramids; optional a priori estimates; outliers; recovered frame-to-frame motion; reference image appearance; reference imagery; retinal slit lamp video; robust multi-frame progressive refinement framework; robust parametric model fit; search range; sensor pose; sparse features; spatial frequency; video registration; video to reference image alignment; Application software; Coordinate measuring machines; Frequency; Image sensors; Lamps; Motion estimation; Parametric statistics; Retina; Robustness; Spatial resolution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on
ISSN :
1063-6919
Print_ISBN :
0-7695-1272-0
Type :
conf
DOI :
10.1109/CVPR.2001.990984
Filename :
990984
Link To Document :
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