NTCIR Lifelog: The First Test Collection for Lifelog Research

Test collections have a long history of supporting repeatable and comparable evaluation in Information Retrieval (IR). However, thus far, no shared test collection exists for IR systems that are designed to index and retrieve multimodal lifelog data. In this paper we introduce the first test col- lection for personal lifelog data. The requirements for such a test collection are motivated, the process of creating the test collection is described, along with an overview of the test collection and finally suggestions are given for possible applications of the test collection, which has been employed for the NTCIR12-Lifelog task

Applying visual user interest profiles for rRecommendation & personalisation

We propose that a visual user interest profile can be generated from images associated with an individual. By employing deep learning, we extract a prototype visual user interest profile and use this as a source for subsequent recommendation and personalisation. We demonstrate this technique via a hotel booking system demonstrator, though we note that there are numerous potential applications

A privacy by design approach to lifelogging

Technologies that enable us to capture and publish data with ease are likely to pose new concerns about privacy of the individual. In this article we exam- ine the privacy implications of lifelogging, a new concept being explored by early adopters, which utilises wearable devices to generate a media rich archive of their life experience. The concept of privacy and the privacy implications of lifelogging are presented and discussed in terms of the four key actors in the lifelogging uni- verse. An initial privacy-aware lifelogging framework, based on the key principles of privacy by design is presented and motivated

Real-time behavioural analysis using google glass

Lifelogging is a form of pervasive computing that represents a phenomenon whereby people can digitally record their own daily lives in varying amounts of detail, for a variety of purposes. Lifelogging offers huge potential for supporting behaviour change because it can capture the totality of life experience and provide heretofore unknown levels of insight into the real-world activities of the lifelogger. In this paper we present a real-time curated lifelogging prototype that can support real-time behavioural analysis by supporting immediate feedback and intervention to the lifelogger

Negative faceblurring: a privacy-by-design approach to visual lifelogging with Google Glass

Wearable devices such as Google Glass are receiving increasing attention and look set to become part of our technical landscape over the next few years. At the same time, lifelogging is a topic that is growing in popularity with a host of new devices on the market that visually capture life experience in an automated manner. We describe a visual lifelogging solution for Google Glass that is designed to capture life experience in rich visual detail, yet maintain the privacy of unknown bystanders

Interactive known-item search using semantic textual and colour modalities

In this paper, we propose an interactive video browser tool for our participation in the fourth video search showcase event. Learning from previous experience, this year we focused on building an advanced interactive interface which allows users to quickly generate and combine different styles of query to find relevant video segments. The system offers the user a comprehensive search interface which has as key features: keyword search, color-region search and human face filtering

Formulating queries for collecting training examples in visual concept classification

Video content can be automatically analysed and indexed using trained classifiers which map low-level features to semantic concepts. Such classifiers need training data consisting of sets of images which contain such concepts and recently it has been discovered that such training data can be located using text-based search to image databases on the internet. Formulating the text queries which locate these training images is the challenge we address here. In this paper we present preliminary results on TRECVid data of concept classification using automatically crawled images as training data and we compare the results with those obtained from manually annotated training sets

LoggerMan, a comprehensive logging and visualisation tool to capture computer usage

As we become increasingly dependent on our computers and spending a major part of our day interacting with these machines, it is becoming important for lifeloggers and human-computer interaction (HCI) researchers to capture this aspect of our life. In this paper, we present LoggerMan, a comprehensive logging tool to capture many aspects of our computer usage. It also comes with reporting capabilities to give insights to the data owner about his/her computer usage. By this work, we aim to fill the current lack of logging software in this domain, which would help us and other researchers as well to build data sets for HCI experiments and also to better understand computer usage patterns. Our tool is published online (loggerman.org) to be used freely by the community

TRECVid 2013 experiments at Dublin City University

In a move away from previous years’ participation in TRECVid ([1] [2] [3]), this year our team focused on the instance search task (INS). We improved our system from last year by applying large vocabulary quantization, soft assignment of visual words, spatial verifications and query expansion. Overall, four automatic runs have been submitted for evaluation. In this paper, we present first our system, then we discuss the results and findings of our experiments

Instance search with weak geometric correlation consistency

Finding object instances from large image collections is a challenging problem with many practical applications. Recent methods inspired by text retrieval achieved good results; however a re-ranking stage based on spatial verification is still required to boost performance. To improve the effectiveness of such instance retrieval systems while avoiding the computational complexity of a re-ranking stage, we explored the geometric correlations among local features and incorporate these correlations with each individual match to form a transformation consistency in rotation and scale space. This weak geometric correlation consistency can be used to effectively eliminate inconsistent feature matches and can be applied to all candidate images at a low computational cost. Experimental results on three standard evaluation benchmarks show that the proposed approach results in a substantial performance improvement compared with recently proposed methods