Information access tasks and evaluation for personal lifelogs

Emerging personal lifelog (PL) collections contain permanent digital records of information associated with individuals’ daily lives. This can include materials such as emails received and sent, web content and other documents with which they have interacted, photographs, videos and music experienced passively or created, logs of phone calls and text messages, and also personal and contextual data such as location (e.g. via GPS sensors), persons and objects present (e.g. via Bluetooth) and physiological state (e.g. via biometric sensors). PLs can be collected by individuals over very extended periods, potentially running to many years. Such archives have many potential applications including helping individuals recover partial forgotten information, sharing experiences with friends or family, telling the story of one’s life, clinical applications for the memory impaired, and fundamental psychological investigations of memory. The Centre for Digital Video Processing (CDVP) at Dublin City University is currently engaged in the collection and exploration of applications of large PLs. We are collecting rich archives of daily life including textual and visual materials, and contextual context data. An important part of this work is to consider how the effectiveness of our ideas can be measured in terms of metrics and experimental design. While these studies have considerable similarity with traditional evaluation activities in areas such as information retrieval and summarization, the characteristics of PLs mean that new challenges and questions emerge. We are currently exploring the issues through a series of pilot studies and questionnaires. Our initial results indicate that there are many research questions to be explored and that the relationships between personal memory, context and content for these tasks is complex and fascinating

Baseline analysis of a conventional and virtual reality lifelog retrieval system

Continuous media capture via a wearable devices is currently one of the most popular methods to establish a comprehensive record of the entirety of an individual's life experience, referred to in the research community as a lifelog. These vast multimodal corpora include visual and other sensor data and are enriched by content analysis, to generate as extensive a record of an individual's life experience. However, interfacing with such datasets remains an active area of research, and despite the advent of new technology and a plethora of competing mediums for processing digital information, there has been little focus on newly emerging platforms such as virtual reality. In this work, we suggest that the increase in immersion and spatial dimensions provided by virtual reality could provide significant benefits to users when compared to more conventional access methodologies. Hence, we motivate virtual reality as a viable method of exploring multimedia archives (specifically lifelogs) by performing a baseline comparative analysis using a novel application prototype built for the HTC Vive and a conventional prototype built for a standard personal computer

Multiple multimodal mobile devices: Lessons learned from engineering lifelog solutions

For lifelogging, or the recording of one’s life history through digital means, to be successful, a range of separate multimodal mobile devices must be employed. These include smartphones such as the N95, the Microsoft SenseCam – a wearable passive photo capture device, or wearable biometric devices. Each collects a facet of the bigger picture, through, for example, personal digital photos, mobile messages and documents access history, but unfortunately, they operate independently and unaware of each other. This creates significant challenges for the practical application of these devices, the use and integration of their data and their operation by a user. In this chapter we discuss the software engineering challenges and their implications for individuals working on integration of data from multiple ubiquitous mobile devices drawing on our experiences working with such technology over the past several years for the development of integrated personal lifelogs. The chapter serves as an engineering guide to those considering working in the domain of lifelogging and more generally to those working with multiple multimodal devices and integration of their data

The role of places and spaces in lifelog retrieval

Finding relevant interesting items when searching or browsing within a large multi-modal personal lifelog archive is a significant challenge. The use of contextual cues to filter the collection and aid in the determination of relevant content is often suggested as means to address such challenges. This work presents an exploration of the various locations, garnered through context logging, several participants engaged in during personal information access over a 15 month period. We investigate the implications of the varying data accessed across multiple locations for context-based retrieval from such collections. Our analysis highlights that a large number of spaces and places may be used for information access, but high volume of content is accessed in few

Exploring Memory Cues to Aid Information Retrieval from Personal LifeLog Archives

The expansion of personal information archives and the emerging field of Personal Lifelogs (PLs) are creating new challenges for information retrieval (IR). While studies have demonstrated the difficulties of IR for these massive data collection [1], we should also think about how we can opportunities and benefits from integrating these data sources as a component of “digital memories” , considering their rich connections with the users‟ memory. We observed that most existing approaches to personal archive IR are mostly technology-driven. Although in recent years studies in Personal Information management (PIM) have claimed to make use of the human memory features, and many works have been reported as investigating well-remembered features of computer files (documents, email, photos). Yet, these explorations are usually confined to the attributes or feature that current computer file systems or technology have provided. I believe that there are important and potentially useful data attributes that these studies have ignored. In addition, current personal search interfaces provide searching options based on what is available in the system, e.g. require users to fill in the calendar date, regardless of the fact that people actually don‟t often encode „time‟ in such a way. My PhD project aims to explore what users actually tend to recall in different personal achieve information seeking tasks, how to present searching options to cater for the right type or format of information that users can recall, and how to exploit this information in an IR system for personal lifelog archives. In this paper, I discuss the limits and advantages of some related work, and present my current and proposed study, with an outlook of an interface that I plan to develop to explore my proposals

Examining the utility of affective response in search of personal lifelogs

Personal lifelog archives contain digital records captured from an individual’s daily life, for example emails, documents edited, webpages downloaded and photographs taken. While capturing this information is becoming increasingly easy, subsequently locating interesting items from within these archives is a significant challenge. One potential source of information to identify items of importance to an individual is their affective state during the capture of the information. The strength of an individual’s affective response to their current situation can often be gauged from their physiological response. For this study we explored the utility of the following biometric features to indicate significant items: galvanic skin response (GSR), heart rate (HR) and skin temperature (ST). Significant or important events tend to raise an individual’s arousal level, causing a measurable biometric response. We examined the utility of using biometric response to identify significant items and for re-ranking traditional information retrieval (IR) result sets. Results obtained indicate that skin temperature is most useful for extracting interesting items from personal archives containing passively captured images, computer activity and SMS messages

Interactive Video Search

With an increasing amount of video data in our daily life, the need for content-based search in videos increases as well. Though a lot of research has been spent on video retrieval tools and methods which allow for automatic search in videos through content-based queries, still the performance of automatic video retrieval is far from optimal. In this tutorial we discussed (i) proposed solutions for improved video content navigation, (ii) typical interaction of content-based querying features, and (iii) advanced video content visualization methods. Moreover, we discussed interactive video search systems and ways to evaluate their performance

Creating stories for reflection from multimodal lifelog content: An initial investigation

Using lifelogging tools, digital artifacts can be collected continuously and passively throughout our day. These may include a stream of images recorded passively using tools such as the Microsoft SenseCam; documents, emails and webpages accessed; texts messages and mobile activity; and context sensing to uncover the current location and proximal individuals. The wealth of information such an archive contains on our personal life history provides us with the opportunity to review, reflect and reminisce upon our past experience. However, the complexity, volume and multimodal nature of such collections creates a barrier to such activities. We are currently exploring the potential of digital narratives formed from these collections as a means to overcome these challenges. By successfully reducing the content to that most appropriate to the story, and by then presenting it in a coherent and usable manner, we can hope to better enable reflection. The means by which content reduction and presentation should occur is investigated through card sorting activities and probe sessions which nine participants engaged in. The initial results are discussed, as well as the opportunity, as seen in these sessions, for lifelog-based stories to provide utility in personal reflection and reminiscence

LifeLogging: personal big data

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 in order to capture life details of life activities, hence we maintain this focus in this review. However, we also reflect on the challenges lifelogging poses to an information retrieval scientist. This review is a suitable reference for those seeking a information retrieval scientist’s perspective on lifelogging and the quantified self