Viewpoint Selection for Taking a good Photograph of Architecture

He, Jingwu; Zhou, Wenzhe; Wang, Linbo; Zhang, Hongjie; Guo, Yanwen

Viewpoint Selection for Taking a good Photograph of Architecture

Files

039-044.pdf (5.61 MB)

Date

2016

Authors

He, Jingwu
Zhou, Wenzhe
Wang, Linbo
Zhang, Hongjie
Guo, Yanwen

Publisher

The Eurographics Association

Abstract

This paper studies the problem of how to choose the viewpoint for taking good photographs for architecture. We achieve this by learning from professional photographs of world famous landmarks that are available in the Internet. Unlike the previous efforts devoted to photo quality assessment which mainly rely on visual features, we show in this paper combining visual features with geometric features computed on the 3D models can result in a more reliable evaluation of viewpoint quality. Specifically, we collect a set of photographs for each of 6 world famous architectures as well as their 3D models from Internet. Viewpoint recovery for images is carried out by an image-model registration process, after which a newly proposed viewpoint clustering strategy is exploited to validate users' viewpoint preference when photographing landmarks. Finally, we extract a number of 2D and 3D features for each image based on multiple visual and geometric cues, and perform viewpoint recommendation by learning from both 2D and 3D features, achieving superior performance over using solely 2D or 3D features. We show the effectiveness of the proposed approach through extensive experiments.

        @inproceedings{10.2312:pg.20161333
,
booktitle = {Pacific Graphics Short Papers
},
editor = {Eitan Grinspun and Bernd Bickel and Yoshinori Dobashi
},
title = {{Viewpoint Selection for Taking a good Photograph of Architecture
}},
author = {He, Jingwu and 
Zhou, Wenzhe and 
Wang, Linbo and 
Zhang, Hongjie and 
Guo, Yanwen
},
year = {2016
},
publisher = {The Eurographics Association
},
ISSN = {-
},
ISBN = {978-3-03868-024-6
},
DOI = {10.2312/pg.20161333
}
}