ICIP 2006, Atlanta, GA
 

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Paper Detail

Paper:MA-P4.11
Session:Image Registration/Alignment and Mosaicking
Time:Monday, October 9, 09:40 - 12:20
Presentation: Poster
Topic: Interpolation and Super-Resolution: Registration / alignment
Title: MULTI-VIEW IMAGE REGISTRATION FOR WIDE-BASELINE VISUAL SENSOR NETWORKS
Authors: Gulcin Caner; University of Rochester 
 A. Murat Tekalp; KoƧ University 
 Gaurav Sharma; University of Rochester 
 Wendi Heinzelman; University of Rochester 
Abstract: We present a new dense multi-view registration technique for wide-baseline video/images that integrates a parametric optical flow-based approach with a sparse set of feature correspondences, based on a locally planar approximation of a nonplanar scene. The proposed method can deal with illuminance variations between the views, which is critically important for wide-baseline applications. It differs from existing work on wide-baseline image registration in that it requires only image information and provides dense matching without computing any camera calibration matrices or performing any prior scene segmentation. These characteristics render the method suitable for practical deployment in visual sensor networks, towards which the current work is directed. We demonstrate the performance of the proposed method on simulated multi-view images of a virtual 3D world composed of piece-wise smooth textured surfaces, as well as real wide-baseline images of nonplanar textured surfaces.