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This paper presents a novel ubiquitous computing device, the Sense-Cam, a sensor augmented wearable stills camera. SenseCam is designed to capture a digital record of the wearer's day, by recording a series of images and capturing a log of sensor data. We believe that reviewing this information will help the wearer recollect aspects of earlier experiences(More)
In current systems for browsing image collections, users are presented with sets of thumbnail images arranged in some default order on the screen. We are investigating whether it benefits users to have sets of thumbnails arranged according to their mutual similarity, so images that are alike are placed together. There are, of course, many possible(More)
The endemic Hawaiian lobeliads are exceptionally species rich and exhibit striking diversity in habitat, growth form, pollination biology and seed dispersal, but their origins and pattern of diversification remain shrouded in mystery. Up to five independent colonizations have been proposed based on morphological differences among extant taxa. We present a(More)
We report on the results of a study using SenseCam, a "life-logging" technology in the form of a wearable camera, which aims to capture data about everyday life in order to support people's memory for past, personal events. We find evidence that SenseCam images do facilitate people's ability to connect to their past, but that images do this in different(More)
A similarity metric based on the low-level content of images can be used to create a visualisation in which visually similar images are displayed close to each other. We are carrying out a series of experiments to evaluate the usefulness of this type of visualisation as an image browsing aid. The initial experiment, described in this paper, considered(More)
We evaluate three different relevance feedback (RF)algorithms, Rocchio, Robertson/Sparck-Jones (RSJ)and Bayesian, in the context of Web search. We use a target-testing experimental procedure whereby a user must locate a specific document. For user relevance feedback, we consider all possible user choices of indicating zero or more relevant documents from a(More)