Lifer

Zhou, Liting; Hinbarji, Zaher; Dang-Nguyen, Duc-Tien; Gurrin, Cathal

doi:10.1145/3210539.3210542

Cited by 19 publications

(1 citation statement)

References 8 publications

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“…Zhou et al [106] proposed an iterative lifelog search engine called LIFER, which is queried based on several different forms of lifelog data, such as visual concepts, activities, locations, time, and so on. Despite some limitations of LIFER, this application allows users to retrieve the moments from their personal life archives in a reliable and efficient manner.…”

Section: Lifelog Retrieval Software Toolsmentioning

confidence: 99%

Lifelog Retrieval From Daily Digital Data: Narrative Review (Preprint)

Ribeiro¹,

Trifan²,

Neves³

2021

Preprint

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BACKGROUND The wide availability and small size, together with the decrease in pricing of different types of sensors, has made it possible, over the last decade, to acquire a huge amount of data about a person's life in real time. These sensors can be incorporated into personal electronic devices available at reasonable cost, such as smartphones and small wearable devices. They allow the acquisition of images, audio, location, physical activity and physiological signals, among other data. With these data, usually denoted as lifelog data, we can then analyze and understand personal experiences and behaviors. This process is called lifelogging. OBJECTIVE The goal of this article is to review the literature in the research area of lifelogging over the past decade and provide an historical overview on this research topic. To this purpose, we analyze lifelogging applications that monitor and assist people with memory problems. METHODS We follow a narrative review methodology to conduct a comprehensive search of relevant publications in Google Scholar and Scopus databases. In order to find these relevant publication, topic-related keywords were identified and combined based on different lifelogging type of data and applications. RESULTS A total of 124 publications were selected and included in this narrative review. 411 publications were retrieved and screened from the two scholar databases. Out of these, 114 publications were fully reviewed. In addition, 32 more publications were manually included based on our bibliographical knowledge in this research field. CONCLUSIONS The use of personal lifelogs can be beneficial to improve the life quality of people suffering from memory problems, such as dementia. Through the acquisition and analysis of lifelog data, lifelogging systems can create digital memories to be used as surrogate memory. Through this narrative we understand that contextual information can be extracted from the lifelogs and it provides significant information for understanding the daily life of people suffering from memory issues based on events, experiences and behaviors.

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Section: Lifelog Retrieval Software Toolsmentioning

confidence: 99%

Lifelog Retrieval From Daily Digital Data: Narrative Review (Preprint)

Ribeiro¹,

Trifan²,

Neves³

2021

Preprint

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A Test Collection for Interactive Lifelog Retrieval

Gurrin

Schoeffmann

Joho

et al. 2018

MultiMedia Modeling

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There is a long history of repeatable and comparable evaluation in Information Retrieval (IR). However, thus far, no shared test collection exists that has been designed to support interactive lifelog retrieval. In this paper we introduce the LSC2018 collection, that is designed to evaluate the performance of interactive retrieval systems. We describe the features of the dataset and we report on the outcome of the first Lifelog Search Challenge (LSC), which used the dataset in an interactive competition at ACM ICMR 2018.

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