Automatically extracting highlights for TV Baseball programs
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
The smart floor: a mechanism for natural user identification and tracking
CHI '00 Extended Abstracts on Human Factors in Computing Systems
Memory cues for meeting video retrieval
Proceedings of the the 1st ACM workshop on Continuous archival and retrieval of personal experiences
Wearable imaging system for summarizing personal experiences
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
The state of the art in image and video retrieval
CIVR'03 Proceedings of the 2nd international conference on Image and video retrieval
Audio visual cues for video indexing and retrieval
PCM'04 Proceedings of the 5th Pacific Rim conference on Advances in Multimedia Information Processing - Volume Part I
Archiving tennis video clips based on tactics information
PCM'04 Proceedings of the 5th Pacific Rim Conference on Advances in Multimedia Information Processing - Volume Part II
Experience retrieval in a ubiquitous home
CARPE '05 Proceedings of the 2nd ACM workshop on Continuous archival and retrieval of personal experiences
Ubiquitous Home: Retrieval of Experiences in a Home Environment
IEICE - Transactions on Information and Systems
Using location, bearing and motion data to filter video and system logs
PERVASIVE'07 Proceedings of the 5th international conference on Pervasive computing
Multimedia retrieval from a large number of sources in a ubiquitous environment
PCM'05 Proceedings of the 6th Pacific-Rim conference on Advances in Multimedia Information Processing - Volume Part I
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A system for video retrieval from a ubiquitous environment is presented. Data from pressure-based floor sensors are used as a supplementary input for retrieving video from a large number of cameras. An algorithm based on agglomerative hierarchical clustering is used to segment footpaths of individual persons. Video handover is proposed and two methods are implemented to retrieve video clips and key frame sequences showing a person moving inside the house. The video clips are further segmented according to the actions performed. We evaluate the performance of each stage of retrieval and present the results. The paper concludes with suggestions for improvements, and future directions.