Publication

Where to go from here? Mobility prediction from instantaneous information

Related publications (32)

Bi-Modal Person Recognition on a Mobile Phone: using mobile phone data

Sébastien Marcel, Norman Hoon Thian Poh, Timothy Cootes

This paper presents a novel fully automatic bi-modal, face and speaker, recognition system which runs in real-time on a mobile phone. The implemented system runs in real-time on a Nokia N900 and demonstrates the feasibility of performing both automatic fac ...

Idiap2012

The Mobile Data Challenge: Big Data for Mobile Computing Research

Daniel Gatica-Perez

This paper presents an overview of the Mobile Data Challenge (MDC), a large-scale research initiative aimed at generating innovations around smartphone-based research, as well as community-based evaluation of related mobile data analysis methodologies. Fir ...

2012

A Regularization Framework for Mobile Social Network Analysis

Pascal Frossard, Pierre Vandergheynst, Xiaowen Dong

Mobile phone data provides rich dynamic information on human activities in social network analysis. In this paper, we represent data from two different modalities as a graph and functions defined on the vertex set of the graph. We propose a regularization ...

2011

A Probabilistic Approach to Socio-Geographic Reality Mining

Katayoun Farrahi

As we live our daily lives, our surroundings know about it. Our surroundings consist of people, but also our electronic devices. Our mobile phones, for example, continuously sense our movements and interactions. This socio-geographic data could be continuo ...

EPFL2011

People-Centric Mobile Sensing with a Pragmatic Twist: from Behavioral Data Points to Active User Involvement

Daniel Gatica-Perez

Mobile phones have recently been used to collect large-scale continuous data about human behavior. This people centric sensing paradigm is useful not only from a scientific point of view: Contextual user data has pragmatic value, too. Individuals whose dat ...

2011

Smartphone usage in the wild: a large-scale analysis of applications and context

Daniel Gatica-Perez

This paper presents a large-scale analysis of contextualized smartphone usage in real life. We introduce two contextual variables that condition the use of smartphone applications, namely places and social context. Our study shows strong dependencies betwe ...

2011

Probabilistic Mining of Socio-Geographic Routines from Mobile Phone Data

Daniel Gatica-Perez, Katayoun Farrahi

There is relatively little work on the investigation of large-scale human data in terms of multimodality for human activity discovery. In this paper we suggest that human interaction data, or human proximity, obtained by mobile phone Bluetooth sensor data, ...

2010

Discovering Human Places of Interest from Multimodal Mobile Phone Data

Daniel Gatica-Perez

In this paper, a new framework to discover places-of-interest from multimodal mobile phone data is presented. Mobile phones have been used as sensors to obtain location information from usersâ€™ real lives. Two levels of clustering are used to obtain place ...

2010

End-to-end adaptation scheme for ubiquitous remote experimentation

Denis Gillet, Christophe Salzmann, Philippe Müllhaupt

Remote experimentation is an effective e-learning paradigm for supporting hands-on education using laboratory equipment at distance. The current trend is to enable remote experimentation in mobile and ubiquitous learning. In such a context, the remote expe ...

2009

Daily Routine Classification from Mobile Phone Data

Daniel Gatica-Perez, Katayoun Farrahi

The automatic analysis of real-life, long-term behavior and dynamics of individuals and groups from mobile sensor data constitutes an emerging and challenging domain. We present a framework to classify people's daily routines (defined by day type, and by g ...

2008

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