Mark Bloess
Abdulmotaleb El Saddik
ABSTRACT
This demo presents a client-server application which collects images and personal information from social networks to build face recognition databases. The client runs on a mobile phone allowing any face captured by a mobile phone's camera to be identified. Using the personal information collected we give back the most meaningful social connection between the user and the recognized individual.
- Facebook Statistics {online} Available: http://newsroom.fb.com/content/default.aspx?NewsAreaId=21.Google Scholar
- Nefian, A.V. 1998. Face detection and recognition using hidden Markov models. In Proceedings of the 1998 International Conference on Image Processing, October 4--7; Chicago USA.Google ScholarCross Ref
- Cohn, D; Hofmann, T. 1999. The Missing Link - A Probabilistic Model of Document Content and Hypertext Connectivity, In Advances in Neural Information Processing Systems 13, 2001.Google Scholar
- Stone, Z., Zickler, T., and Darrell, T. 2010. Toward large-scale face recognition using social network context. In Proceedings of the IEEE 98, 8, 1408--1415.Google ScholarCross Ref
- OpenCV: Open Source Computer Vision Library, {online} Available: http://opencv.willowgarage.com/wiki/Google Scholar
- Barbehenn, M. 1998. A note on the complexity of Dijkstra's algorithm for graphs with weighted vertices. IEEE Transactions on Computers 47, 2, 26 Google ScholarDigital Library
Index Terms
- PhacePhinder: harnessing social networks to build social face databases for mobile devices
Recommendations
Social Network Services as Data Sources and Platforms for e-Researching Social Networks
Social network services such as Facebook provide new data for social science research into, for example, the role of individual characteristics in friendship formation and the diffusion of tastes in social networks. This article assesses the potential ...
Face recognition under varying illumination using gradientfaces
In this correspondence, we propose a novel method to extract illumination insensitive features for face recognition under varying lighting called the Gradientfaces. Theoretical analysis shows Gradientfaces is an illumination insensitive measure, and ...
Analysis of Facebook Social Network
CICN '13: Proceedings of the 2013 5th International Conference on Computational Intelligence and Communication NetworksSocial Network Analysis (SNA) is a technique for modeling the communication patterns between individuals in a way that illuminates the structure of the network and the importance of individuals within the network. SNA has gained a recent importance due ...
Comments