Providing effective memory retrieval cues through automatic structuring and augmentation of a lifelog of images

Lifelogging is an area of research which is concerned with the capture of many aspects of an individual's life digitally, and within this rapidly emerging field is the significant challenge of managing images passively captured by an individual of their daily life. Possible applications vary from helping those with neurodegenerative conditions recall events from memory, to the maintenance and augmentation of extensive image collections of a tourist's trips. However, a large lifelog of images can quickly amass, with an average of 700,000 images captured each year, using a device such as the SenseCam. We address the problem of managing this vast collection of personal images by investigating automatic techniques that: 1. Identify distinct events within a full day of lifelog images (which typically consists of 2,000 images) e.g. breakfast, working on PC, meeting, etc. 2. Find similar events to a given event in a person's lifelog e.g. "show me other events where I was in the park" 3. Determine those events that are more important or unusual to the user and also select a relevant keyframe image for visual display of an event e.g. a "meeting" is more interesting to review than "working on PC" 4. Augment the images from a wearable camera with higher quality images from external "Web 2.0" sources e.g. find me pictures taken by others of the U2 concert in Croke Park In this dissertation we discuss novel techniques to realise each of these facets and how effective they are. The significance of this work is not only of benefit to the lifelogging community, but also to cognitive psychology researchers studying the potential benefits of lifelogging devices to those with neurodegenerative diseases

Digital life stories: Semi-automatic (auto)biographies within lifelog collections

Our life stories enable us to reflect upon and share our personal histories. Through emerging digital technologies the possibility of collecting life experiences digitally is increasingly feasible; consequently so is the potential to create a digital counterpart to our personal narratives. In this work, lifelogging tools are used to collect digital artifacts continuously and passively throughout our day. These include images, documents, emails and webpages accessed; texts messages and mobile activity. This range of data when brought together is known as a lifelog. Given the complexity, volume and multimodal nature of such collections, it is clear that there are significant challenges to be addressed in order to achieve coherent and meaningful digital narratives of our events from our life histories. This work investigates the construction of personal digital narratives from lifelog collections. It examines the underlying questions, issues and challenges relating to construction of personal digital narratives from lifelogs. Fundamentally, it addresses how to organize and transform data sampled from an individual’s day-to-day activities into a coherent narrative account. This enquiry is enabled by three 20-month long-term lifelogs collected by participants and produces a narrative system which enables the semi-automatic construction of digital stories from lifelog content. Inspired by probative studies conducted into current practices of curation, from which a set of fundamental requirements are established, this solution employs a 2-dimensional spatial framework for storytelling. It delivers integrated support for the structuring of lifelog content and its distillation into storyform through information retrieval approaches. We describe and contribute flexible algorithmic approaches to achieve both. Finally, this research inquiry yields qualitative and quantitative insights into such digital narratives and their generation, composition and construction. The opportunities for such personal narrative accounts to enable recollection, reminiscence and reflection with the collection owners are established and its benefit in sharing past personal experience experiences is outlined. Finally, in a novel investigation with motivated third parties we demonstrate the opportunities such narrative accounts may have beyond the scope of the collection owner in: personal, societal and cultural explorations, artistic endeavours and as a generational heirloom

An Advanced A-V- Player to Support Scalable Personalised Interaction with Multi-Stream Video Content

PhDCurrent Audio-Video (A-V) players are limited to pausing, resuming, selecting and viewing a single video stream of a live broadcast event that is orchestrated by a professional director. The main objective of this research is to investigate how to create a new custom-built interactive A V player that enables viewers to personalise their own orchestrated views of live events from multiple simultaneous camera streams, via interacting with tracked moving objects, being able to zoom in and out of targeted objects, and being able to switch views based upon detected incidents in specific camera views. This involves research and development of a personalisation framework to create and maintain user profiles that are acquired implicitly and explicitly and modelling how this framework supports an evaluation of the effectiveness and usability of personalisation. Personalisation is considered from both an application oriented and a quality supervision oriented perspective within the proposed framework. Personalisation models can be individually or collaboratively linked with specific personalisation usage scenarios. The quality of different personalised interaction in terms of explicit evaluative metrics such as scalability and consistency can be monitored and measured using specific evaluation mechanisms.European Union's Seventh Framework Programme ([FP7/2007-2013]) under grant agreement No. ICT- 215248 and from Queen Mary University of London