Investigating keyframe selection methods in the novel domain of passively captured visual lifelogs
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
Identifying Different Settings in a Visual Diary
WIAMIS '08 Proceedings of the 2008 Ninth International Workshop on Image Analysis for Multimedia Interactive Services
SenseCam: a retrospective memory aid
UbiComp'06 Proceedings of the 8th international conference on Ubiquitous Computing
Combining image descriptors to effectively retrieve events from visual lifelogs
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
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The SenseCam is a wearable camera that passively captures images. Therefore, it requires no conscious effort by a user in taking a photo. A Visual Diary from such a source could prove to be a valuable tool in assisting the elderly, individuals with neurodegenerative diseases, or other traumas. One issue with Visual Lifelogs is the large volume of image data generated. In previous work, we segmented a day's worth of images into more manageable segments, i.e. into distinct events or activities. However, each event could still consist of 80-100 images, thus, in this paper we propose a novel approach to selecting the key images within an event using a combination of MPEG-7 and Scale Invariant Feature Transform (SIFT) features.