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ICMCS
2008
IEEE
207views Multimedia» more  ICMCS 2008»
14 years 2 months ago
Structure learning in a Bayesian network-based video indexing framework
Several stochastic models provide an effective framework to identify the temporal structure of audiovisual data. Most of them need as input a first video structure, i.e. connecti...
Siwar Baghdadi, Guillaume Gravier, Claire-Hé...
CVPR
2000
IEEE
14 years 9 months ago
Impact of Dynamic Model Learning on Classification of Human Motion
The human figure exhibits complex and rich dynamic behavior that is both nonlinear and time-varying. However, most work on tracking and analysis of figure motion has employed eith...
Vladimir Pavlovic, James M. Rehg
COMPSEC
2004
91views more  COMPSEC 2004»
13 years 7 months ago
Predicting the intrusion intentions by observing system call sequences
Identifying the intentions or attempts of the monitored agents through observations is very vital in computer network security. In this paper, a plan recognition method for predict...
Li Feng, Xiaohong Guan, Sangang Guo, Yan Gao, Pein...
ICML
2004
IEEE
14 years 8 months ago
Dynamic conditional random fields: factorized probabilistic models for labeling and segmenting sequence data
In sequence modeling, we often wish to represent complex interaction between labels, such as when performing multiple, cascaded labeling tasks on the same sequence, or when longra...
Charles A. Sutton, Khashayar Rohanimanesh, Andrew ...
HUC
2010
Springer
13 years 7 months ago
Bayesian recognition of motion related activities with inertial sensors
This work presents the design and evaluation of an activity recognition system for seven important motion related activities. The only sensor used is an Inertial Measurement Unit ...
Korbinian Frank, Maria Josefa Vera Nadales, Patric...