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 knownitem 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.

Current online handwriting recognition systems have very limited error recovery mechanisms. In this paper, we discuss the problem of error repair in an online handwriting interface. Based on user study of common repair patterns found in human handwriting, we propose an approach that allows users to recover from recognition errors. The basic idea is to handle the error repair at the interface level by interacting with users. The method requires few modifications on original recognition engine and imposes few restrictions on users. We have developed a prototype system to demonstrate the proposed concept and perform user study when the system provides error recovery mechanisms.

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We present a research proposal that investigates the use of 3D representations in Augmented Reality (AR) to allow neuroscientists to explore literature they wish to understand for their own scientific purposes. Neuroscientists need to identify potential real-life experiments they wish to perform that provide the most information for their field with the minimum use of limited resources. This requires understanding both the alreadyknown relationships among concepts and those that have not yet been discovered. Our assumption is that by providing overviews of the correlations among concepts through the use of linked data, these will allow neuroscientists to better understand the gaps in their own literature and more quickly identify the most suitable experiments to carry out. We will identify candidate visualizations and improve upon these for a specific information need. We describe our planned prototype 3D AR implementation and directions we intend to explore.

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