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CVIU
2004
132views more  CVIU 2004»
14 years 11 months ago
Layered representations for learning and inferring office activity from multiple sensory channels
We present the use of layered probabilistic representations for modeling human activities, and describe how we use the representation to do sensing, learning, and inference at mul...
Nuria Oliver, Ashutosh Garg, Eric Horvitz
IJCV
2008
167views more  IJCV 2008»
14 years 11 months ago
Learning Layered Motion Segmentations of Video
We present an unsupervised approach for learning a generative layered representation of a scene from a video for motion segmentation. The learnt model is a composition of layers, ...
M. Pawan Kumar, Philip H. S. Torr, Andrew Zisserma...
DBSEC
1996
125views Database» more  DBSEC 1996»
15 years 10 days ago
A Framework for High Assurance Security of Distributed Objects
High assurance security is di cult to achieve in distributed computer systems and databases because of their complexity, non-determinism and inherent heterogeneity. The practical ...
John Hale, Jody Threet, Sujeet Shenoi
CORR
2008
Springer
173views Education» more  CORR 2008»
14 years 11 months ago
Decomposition Principles and Online Learning in Cross-Layer Optimization for Delay-Sensitive Applications
In this paper, we propose a general cross-layer optimization framework in which we explicitly consider both the heterogeneous and dynamically changing characteristics of delay-sens...
Fangwen Fu, Mihaela van der Schaar
CLOR
2006
15 years 2 months ago
Sequential Learning of Layered Models from Video
Abstract. A popular framework for the interpretation of image sequences is the layers or sprite model, see e.g. [1], [2]. Jojic and Frey [3] provide a generative probabilistic mode...
Michalis K. Titsias, Christopher K. I. Williams