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» Activity Modeling Using Event Probability Sequences
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152
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ADBIS
2009
Springer
151views Database» more  ADBIS 2009»
15 years 8 months ago
Rule-Based Management of Schema Changes at ETL Sources
In this paper, we visit the problem of the management of inconsistencies emerging on ETL processes as results of evolution operations g at their sources. We abstract Extract-Transf...
George Papastefanatos, Panos Vassiliadis, Alkis Si...
3DIM
1999
IEEE
15 years 6 months ago
Appearance-Based Virtual View Generation of Temporally-Varying Events from Multi-Camera Images in the 3D Room
In this paper, we present an "appearance-based" virtual view generation method for temporally-varying events taken by multiple cameras of the "3D Room", develo...
Hideo Saito, Shigeyuki Baba, Makoto Kimura, Sundar...
125
Voted
ICPR
2006
IEEE
16 years 3 months ago
Event Recognition with Fragmented Object Tracks
Complete and accurate video tracking is very difficult to achieve in practice due to long occlusions, traffic clutter, shadows and appearance changes. In this paper, we study the ...
Anthony Hoogs, Gianfranco Doretto, John Schmiedere...
157
Voted
CVPR
1998
IEEE
16 years 4 months ago
Using Adaptive Tracking to Classify and Monitor Activities in a Site
We describe a vision system that monitors activity in a site over extended periods of time. The system uses a distributed set of sensors to cover the site, and an adaptive tracker...
W. Eric L. Grimson, Chris Stauffer, R. Romano, L. ...
134
Voted
ICML
2000
IEEE
16 years 3 months ago
Maximum Entropy Markov Models for Information Extraction and Segmentation
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...
Andrew McCallum, Dayne Freitag, Fernando C. N. Per...