Video Retrieval by Feature Learning in Key Frames
CIVR '02 Proceedings of the International Conference on Image and Video Retrieval
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
A usage study of retrieval modalities for video shot retrieval
Information Processing and Management: an International Journal
Key frame selection by motion analysis
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 02
Using Graphics Processor Units (GPUs) for Automatic Video Structuring
WIAMIS '07 Proceedings of the Eight International Workshop on Image Analysis for Multimedia Interactive Services
Split-screen dynamically accelerated video summaries
Proceedings of the international workshop on TRECVID video summarization
Combining Face Detection and Novelty to Identify Important Events in a Visual Lifelog
CITWORKSHOPS '08 Proceedings of the 2008 IEEE 8th International Conference on Computer and Information Technology Workshops
Automatically Segmenting LifeLog Data into Events
WIAMIS '08 Proceedings of the 2008 Ninth International Workshop on Image Analysis for Multimedia Interactive Services
An examination of a large visual lifelog
AIRS'08 Proceedings of the 4th Asia information retrieval conference on Information retrieval technology
SenseCam: a retrospective memory aid
UbiComp'06 Proceedings of the 8th international conference on Ubiquitous Computing
Investigating biometric response for information retrieval applications
ECIR'06 Proceedings of the 28th European conference on Advances in Information Retrieval
Adding Semantics to Detectors for Video Retrieval
IEEE Transactions on Multimedia
Keyframe detection in visual lifelogs
Proceedings of the 1st international conference on PErvasive Technologies Related to Assistive Environments
Combining image descriptors to effectively retrieve events from visual lifelogs
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Validating the Detection of Everyday Concepts in Visual Lifelogs
SAMT '08 Proceedings of the 3rd International Conference on Semantic and Digital Media Technologies: Semantic Multimedia
A Framework for Review, Annotation, and Classification of Continuous Video in Context
SG '09 Proceedings of the 10th International Symposium on Smart Graphics
Detecting Significant Events in Lecture Video using Supervised Machine Learning
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
Now let me see where i was: understanding how lifelogs mediate memory
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Everyday concept detection in visual lifelogs: validation, relationships and trends
Multimedia Tools and Applications
Aggregating semantic concepts for event representation in lifelogging
Proceedings of the International Workshop on Semantic Web Information Management
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The SenseCam is a passive capture wearable camera 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 a 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. We propose a novel keyframe selection technique which seeks to select the image with the highest "quality" as the keyframe. The inclusion of "quality" approaches in keyframe selection is demonstrated to be useful owing to the high variability in image visual quality within passively captured image collections.