Investigating keyframe selection methods in the novel domain of passively captured visual lifelogs

The SenseCam is a passive capture wearable camera, worn around the neck, and when worn continuously it takes an average of 1,900 images per day. It can be used to create a personal lifelog or visual recording of the wearer's life which can be helpful as an aid to human memory. For such a large amount of visual information to be useful, it needs to be structured into "events", which can be achieved through automatic segmentation. An important component of this structuring process is the selection of keyframes to represent individual events. This work investigates a variety of techniques for the selection of a single representative keyframe image from each event, in order to provide the user with an instant visual summary of that event. In our experiments we use a large test set of 2,232 lifelog events collected by 5 users over a time period of one month each (equating to 194,857 images). We propose a novel keyframe selection technique which seeks to select the image with...

• Type: Conference
• Year: 2008
• Where: CIVR
• Authors: Aiden R. Doherty, Daragh Byrne, Alan F. Smeaton, Gareth J. F. Jones, Mark Hughes
• Keywords: CIVR 2008, Image Analysis, Keyframe Selection, Keyframe Selection Technique, Representative Keyframe Image