Phorec: Context-Aware Photography Support System Based on Social Data Analysis

In the world of digital photography, it is widely known that general contexts including location, date, time, weather condition, composition, and camera setting, obviously affect quality of photos. In this paper, we analyzed the crowdsourced big data on the social network for photographers and extracted the rich photographic information in order to assist photographers to take beautiful photos. Our developed system is composed of server-side system and mobile application. The server-side system suggests good photos which are relevant to the contexts. The sophisticated iOS application was developed to collect the contexts and exhibit the result. The user’s satisfaction in Phorec were measured through subjective evaluations. The result reflected that recommended photography settings are important and can fulfil user’s desire.

[1]  Barry Smyth,et al.  The social camera: a case-study in contextual image recommendation , 2011, IUI '11.

[2]  Slava Kisilevich,et al.  Towards Acquisition of Semantics of Places and Events by Multi-perspective Analysis of Geotagged Photo Collections , 2013 .

[3]  W. Chu Studying Aesthetics in Photographic Images Using a Computational Approach , 2013 .

[4]  Jiebo Luo,et al.  Photo classification by integrating image content and camera metadata , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[5]  Tao Mei,et al.  Finding perfect rendezvous on the go: accurate mobile visual localization and its applications to routing , 2012, ACM Multimedia.

[6]  C. Robusto The Cosine-Haversine Formula , 1957 .

[7]  Florian Lemmerich,et al.  Describing Locations Using Tags and Images: Explorative Pattern Mining in Social Media , 2011, MSM/MUSE.

[8]  J. C. Platt AutoAlbum: clustering digital photographs using probabilistic model merging , 2000, 2000 Proceedings Workshop on Content-based Access of Image and Video Libraries.

[9]  Jianping Fan,et al.  JustClick: Personalized Image Recommendation via Exploratory Search From Large-Scale Flickr Images , 2009, IEEE Transactions on Circuits and Systems for Video Technology.

[10]  Steffen Staab,et al.  Exploiting Flickr Tags and Groups for Finding Landmark Photos , 2009, ECIR.

[11]  James Ze Wang,et al.  Studying Aesthetics in Photographic Images Using a Computational Approach , 2006, ECCV.

[12]  Barbara Scifo,et al.  The Sociocultural Forms of Mobile Personal Photographs in a Cross-Media Ecology: Reflections Starting from the Young Italian Experience , 2009 .

[13]  Daniel Cohen-Or,et al.  Optimizing Photo Composition , 2010, Comput. Graph. Forum.

[14]  Steven Van Canneyt,et al.  Time-dependent recommendation of tourist attractions using Flickr , 2011 .