NDLI: Local homography estimation using keypoint descriptors

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Local homography estimation using keypoint descriptors

Content Provider	IEEE Xplore Digital Library
Author	Del Bimbo, A. Franco, F. Pernici, F.
Copyright Year	2010
Description	Author affiliation: Media Integration and Communication Center (MICC), University of Florence, Italy (Del Bimbo, A.; Franco, F.; Pernici, F.)
Abstract	This paper presents a new learning-based approach to estimate local homography of a given 3D object and shows that it ismore accurate than specific affine region detection methods. Unlike the previous works that attempt this by adapting iterative algorithms, our method introduces a direct estimation. It performs in three step. First, a training set of features captures geometry and appearance information about keypoints taken from multiple views of the object. Then incoming keypoints are matched against the database in order to retrieve a cluster of features representing their identity. Finally the retrieved clusters are used to estimate the local pose of the patches.
Starting Page	1
Ending Page	4
File Size	693022
Page Count	4
File Format	PDF
ISBN	9781424478484
e-ISBN	9788890532801
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-04-12
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Univ of Brescia
Subject Keyword	Silicon Indexing
Content Type	Text
Resource Type	Article

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