Paper Info
Title
Socialized Mobile Photography: Learning to Photograph With Social Context via Mobile Devices
Abstract
The popularity of mobile devices equipped with various cameras has revolutionized modern photography. People are able to take photos and share their experiences anytime and anywhere. However, taking a high quality photograph via mobile device remains a challenge for mobile users. In this paper we investigate a photography model to assist mobile users in capturing high quality photos by using both the rich context available from mobile devices and crowdsourced social media on the Web. The photography model is learned from community-contributed images on the Web, and dependent on user's social context. The context includes user's current geo-location, time (i.e., time of the day), and weather (e.g., clear, cloudy, foggy, etc.). Given a wide view of scene, our socialized mobile photography system is able to suggest the optimal view enclosure (composition) and appropriate camera parameters (aperture, ISO, and exposure time). Extensive experiments have been performed for eight well-known hot spot landmark locations where sufficient context tagged photos can be obtained. Through both objective and subjective evaluations, we show that the proposed socialized mobile photography system can indeed effectively suggest proper composition and camera parameters to help the user capture high quality photos.
Year
DOI
Venue
2014
10.1109/TMM.2013.2283468
IEEE Transactions on Multimedia
Keywords
Field
DocType
Mobile communication,Photography,Context,Cameras,Mobile handsets,Apertures,Meteorology
Mobile technology,Mobile computing,Computer vision,Mobile search,Digital photography,Social media,Computer science,Mobile device,Photography,Artificial intelligence,Mobile Web,Multimedia
Journal
Volume
Issue
ISSN
16
1
1520-9210
Citations 
PageRank 
References 
22
0.98
25
Authors
4
Name
Order
Citations
PageRank
Wenyuan Yin1604.28
Tao Mei24702288.54
Chang Wen Chen32973263.89
Shipeng Li43902252.94