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2015 | OriginalPaper | Buchkapitel

5. Visual Applications

verfasst von : Bin Fan, Zhenhua Wang, Fuchao Wu

Erschienen in: Local Image Descriptor: Modern Approaches

Verlag: Springer Berlin Heidelberg

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Abstract

Local image descriptors have been widely used in many computer vision applications such as 3D reconstruction, object detection and recognition, image stitch, image retrieval, and localization etc. to name a few. In this chapter, we will introduce some of them, and show how a robust and discriminative descriptor is used in these specific applications.

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Vorheriges Kapitel Burgeoning Methods: Binary Descriptors

Nächstes Kapitel Resources and Future Work

In the time when the Photo Tourism [39] (a milestone work of large-scale image-based 3D reconstruction) was proposed, SIFT was still the best available technique for establishing point correspondences. The quality of feature matching achieved by SIFT is capable of reconstructing most scenes, so it is still a first choice up to now.

The Bundler software used in Photo Tourism for structure from motion can be downloaded from http://www.cs.cornell.edu/~snavely/bundler/.

The PMVS is available on http://www.di.ens.fr/cmvs/.

In the task of specific object recognition, the database storing object images is usually not very large.

A keyframe is defined to be connected to another when the number of their common map points exceeds a predefined threshold.

A reference keyframe of a frame is the keyframe shares most map points with the frame.

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Titel: Visual Applications
verfasst von: Bin Fan
Zhenhua Wang
Fuchao Wu
Verlag: Springer Berlin Heidelberg
Buch: Local Image Descriptor: Modern Approaches
Print ISBN: 978-3-662-49171-3

Electronic ISBN: 978-3-662-49173-7

Copyright-Jahr: 2015
DOI: https://doi.org/10.1007/978-3-662-49173-7_5

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