LSC '18: Proceedings of the 2018 ACM Workshop on The Lifelog Search Challenge

Lifelogging is becoming an increasingly important topic of research and this paper highlights the thoughts of the three panelists at the LSC - Lifelog Search Challenge at ICMR 2018 in Yokohama, Japan on June 11, 2018. The thoughts cover important topics such as the need for challenges in multimedia access, the need for a better user interface and the challenges in building datasets and organising benchmarking activities such as the LSC.

With the growing hype for wearable devices recording biometric data comes the readiness to capture and combine even more personal information as a form of digital diary - lifelogging today is practiced ever more and can be categorized anywhere between an informative hobby and a life-changing experience. From an information processing point of view, analyzing the entirety of such multi-source data is immensely challenging, which is why the first Lifelog Search Challenge 2018 competition is brought into being, as to encourage the development of efficient interactive data retrieval systems. Answering this call, we present a retrieval system based on our video search system diveXplore, which has successfully been used in the Video Browser Showdown 2017 and 2018. Due to the different task definition and available data corpus, the base system was adapted and extended to this new challenge. The resulting lifeXplore system is a flexible retrieval and exploration tool that offers various easy-to-use, yet still powerful search and browsing features that have been optimized for lifelog data and for usage by novice users. Besides efficient presentation and summarization of lifelog data, it includes searchable feature maps, concept and metadata filters, similarity search and sketch search.

In this paper, we introduce a first generation interactive lifelog search engine called \systemname, a system that allows a user to retrieve the moments from the personal life archives in a reliable and efficient manner. We designed this system to assist a user in examining their life experience to gain insights into their activities and lifestyle. We also discuss how this interactive search engine performs over the six LSC development topics.

Known-item search in multimodal lifelog data represents a challenging task for present search engines. Since sequences of temporally close images represent a significant part of the provided data, an interactive video retrieval tool with few extensions could be confronted at Lifelog Search Challenge in known-item search tasks. We present an update of the SIRET interactive video retrieval tool that recently won the Video Browser Showdown 2018. As the tool relies on frame-based representations and retrieval models, it can be directly used also for images from lifelog cameras. The updates comprise mostly visualization and navigation methods for a high number of visually similar scenes representing repetitive daily activities.

The Lifelog Search Challenge (LSC) invites researchers to share their prototypes for lifelog exploration and retrieval and encourages competition to evaluate effective methodologies for this. In this paper. we present a novel approach to visual lifelog exploration using a virtual reality (VR) platform. Findings from our initial experiments with known-item search from lifelog data have motivated us to build a retrieval engine for virtual reality that uses visual concepts automatically extracted from the lifelog visual data as the basis for it's filtering mechanism.

Lifelogging data provides useful insight understanding about our lives during daily activities. Thus, it is essential to develop a system to assist users to retrieve events or memories from lifelogging data from ad-hoc text queries. In this paper, we first propose a method to process lifelogging data by grouping images into visual shots and clusters, then extract semantic concepts on scene category and attributes, entities, and actions. We then develop a query system that supports 4 main types of query conditions: temporal, spatial, entity and action, and extra data criteria. Our system is expected to efficiently assist users to search for past moments in daily logs.

In this work, we describe an interactive lifelog search engine developed for the LSC 2018 search challenge at ACM ICMR 2018. The paper introduces the four-step process required to support lifelog search engines and describes the source data for the search engine as well as the approach to ranking chosen for the iterative search engine. Finally the interface used is introduced before we highlight the limits of the current prototype and suggest opportunities for future work.

We present a virtual reality system for accessing geotagged photos taken with a lifelogging camera. Photos are spatially located on a world map that can be explored with a head-mounted display. Using a virtual reality headset allows users to easily and intuitively explore this large information space. Images are initially represented by icons but become visible once a user gets closer to a particular area of interest. While not suitable for all search tasks, this visualisation has benefits in situations where location plays a significant role; be it because the actual content is location-related or because the owner of the lifelog remembers and associates the related event with certain places. Likewise, our spatial representation of the data often implicitly reveals a temporal relationship, which can be helpful in the search process as well.