Fotofiti

Lee, Benjamin N.; Chen, Wen-Yen; Chang, Edward Yi

doi:10.1145/1180639.1180737

Cited by 6 publications

(1 citation statement)

References 5 publications

(1 reference statement)

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“…This problem is recognized as difficult, especially under severe viewpoint changes between images. This is a fundamental step in many computer vision and image processing applications such as scene recognition [73,7,66,12,44,65,74,21,79,45] and detection [18,51], object tracking [81], robot localization [67,72,48,5,52], image stitching [2,6], image registration [78,30] and retrieval [22,20], 3D modeling and reconstruction [15,19,75,1,57], motion estimation [76], photo management [68,77,27,9], symmetry detection [32] or even image forgeries detection [10].…”

Section: Introductionmentioning

confidence: 99%

Robust Homography Estimation from Local Affine Maps

Rodríguez¹,

Facciolo²,

Morel³

2023

Image Processing on Line

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The corresponding point coordinates determined by classic image matching approaches define local zero-order approximations of the global mapping between two images. But the patches around keypoints typically contain more information, which may be exploited to obtain a firstorder approximation of the mapping, incorporating local affine maps between corresponding keypoints. Several methods have been proposed in the literature to compute this first-order approximation. In this paper we present several modifications of the RANSAC (RANdom SAmple Consensus) algorithm, that uses affine approximations and a-contrario procedures to improve the homography estimation between a pair of images. The a-contrario methodology provides a definition of the soundness of an estimation and allows for adaptive thresholds for inlier/outlier discrimination. These approaches outperform the state-of-the-art for different choices of image descriptors and image datasets, and permit to increase the probability of success in identifying image pairs in challenging matching databases. Source CodeThe reviewed and documented source code and an online demo are available at the web page of this article 1 . Compilation and usage instructions are included in the README.md file of the archive.

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Section: Introductionmentioning

confidence: 99%

Robust Homography Estimation from Local Affine Maps

Rodríguez¹,

Facciolo²,

Morel³

2023

Image Processing on Line

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Do Gender and Age Matter? A User Study on Differences in Photo Collection Management

Ziesemer

Bergmann

Manssour

et al. 2014

Human-Computer Interaction. Applications and Services

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Semantic Multimedia

et al. 2008

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Multimedia constitutes an interesting field of application for Semantic Web and Semantic Web reasoning, as the access and management of multimedia content and context depends strongly on the semantic descriptions of both. At the same time, multimedia resources constitute complex objects, the descriptions of which are involved and require the foundation on sound modeling practice in order to represent findings of low-and high level multimedia analysis and to make them accessible via Semantic Web querying of resources. This tutorial aims to provide a red thread through these different issues and to give an outline of where Semantic Web modeling and reasoning needs to further contribute to the area of semantic multimedia for the fruitful interaction between these two fields of computer science.

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Fotofiti

Cited by 6 publications

References 5 publications

Robust Homography Estimation from Local Affine Maps

Robust Homography Estimation from Local Affine Maps

Do Gender and Age Matter? A User Study on Differences in Photo Collection Management

Semantic Multimedia

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