LifeLogging: Personal Big Data

By Cathal Gurrin, Alan F. Smeaton, Aiden R. Doherty. Foundations and Trends in Information Retrieval, 2014

496 citations recorded by the source corpus.

We have recently observed a convergence of technologies to foster the emergence of lifelogging as a mainstream activity. Computer storage has become significantly cheaper, and advancements in sensing technology allows for the efficient sensing of personal activities, locations and the environment. This is best seen in the growing popularity of the quantified self movement, in which life activities are tracked using wearable sensors in the hope of better understanding human performance in a variety of tasks. This review aims to provide a comprehensive summary of lifelogging, to cover its research history, current technologies, and applications. Thus far, most of the lifelogging research has focused predominantly on visual lifelogging, hence we maintain this focus in this review. However, we also reflect on the challenges lifelogging poses for information access and retrieval in general. This review is a suitable reference for those seeking an information retrieval scientist's perspective on lifelogging and the quantified self.

Subfields: Computer Networks and Communications, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/0246edc6c018faa245e1ec88ba0fe916be2c3081

Citations in the corpus

• Computer Vision and Image Understanding Computer Vision for Assistive Technologies (unknown): “In this context the representation of semantic concepts appearing in visual lifelogs is a fundamental step since the huge amount of data collected by a user over time (personal big data) ( Gurrin et al., 2014; Wang et al., 2016 ).”