Exquisitor at the Lifelog Search Challenge 2020

We present an enhanced version of Exquisitor, our interactive and scalable media exploration system. At its core, Exquisitor is an interactive learning system using relevance feedback on media items to build a model of the users' information need. Relying on efficient media representation and indexing, it facilitates real-time user interaction. The new features for the Lifelog Search Challenge 2020 include support for timeline browsing, search functionality for finding positive examples, and significant interface improvements. Participation in the Lifelog Search Challenge allows us to compare our paradigm, relying predominantly on interactive learning, with more traditional search-based multimedia retrieval systems

VRLE: Lifelog Interaction Prototype in Virtual Reality:Lifelog Search Challenge at ACM ICMR 2020

The Lifelog Search Challenge (LSC) invites researchers to share their prototypes for interactive lifelog retrieval and encourages competition to develop and evaluate effective methodologies to achieve this. With this paper we present a novel approach to visual lifelog exploration based on our research to date utilising virtual reality as a medium for interactive information retrieval. The VRLE prototype presented is an iteration on a previous system which won the first LSC competition at ACM ICMR 2018

An Interactive Lifelog Search Engine for LSC2018

This thesis consists on developing an interactive lifelog search engine for the LSC 2018 search challenge at ACM ICMR 2018. This search engine is created in order to browse for images from a given lifelog dataset and display them along with some written information related to them and four other images providing contextualization about the searched one. First of all, the work makes an introduction to the relevance of this project. It introduces the reader to the main social problems affronted and the aim of our project to deal with them. Thus, go ahead with the scope of the project introducing to the main objectives fixed. Also, the work is gone by the actual state of the same kind of prototypes that already exist to let the reader see the differences that our project presents. After the project approach is done, it begins a travel trough the methodology and creation process, going deep in the main aspects and the explanation of every election and decision, also remarking the limits of the current prototype. Additionally, the project concludes with a result section where the system is tested with six users. They are asked to find three specific images using the search engine. This test is divided in two sections: first, a qualitative section where the user is asked to test the system and fill out a survey to see how comfortable it is for him. And a second section, more quantitative, where they value the speed of our system. Finally, the project concludes going through the actual and future ethics of lifelogging in general and with a final conclusion further investigation and future improvemen

FIRST - Flexible interactive retrieval SysTem for visual lifelog exploration at LSC 2020

Lifelog can provide useful insights of our daily activities. It is essential to provide a flexible way for users to retrieve certain events or moments of interest, corresponding to a wide variation of query types. This motivates us to develop FIRST, a Flexible Interactive Retrieval SysTem, to help users to combine or integrate various query components in a flexible manner to handle different query scenarios, such as visual clustering data based on color histogram, visual similarity, GPS location, or scene attributes. We also employ personalized concept detection and image captioning to enhance image understanding from visual lifelog data, and develop an autoencoderlike approach for query text and image feature mapping. Furthermore, we refine the user interface of the retrieval system to better assist users in query expansion and verifying sequential events in a flexible temporal resolution to control the navigation speed through sequences of images

Memento: a prototype lifelog search engine for LSC’21

In this paper, we introduce a new lifelog retrieval system called Memento that leverages semantic representations of images and textual queries projected into a common latent space to facilitate effective retrieval. It bridges the semantic gap between complex visual scenes/events and user information needs expressed as textual and faceted queries. The system, developed for the 2021 Lifelog Search Challenge also has a minimalist user interface that includes primary search, temporal search, and visual data filtering components