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CVPR
1999
IEEE
16 years 8 months ago
Time-Series Classification Using Mixed-State Dynamic Bayesian Networks
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huan...
ICTIR
2009
Springer
16 years 1 months ago
Modeling the Score Distributions of Relevant and Non-relevant Documents
Empirical modeling of the score distributions associated with retrieved documents is an essential task for many retrieval applications. In this work, we propose modeling the releva...
Evangelos Kanoulas, Virgiliu Pavlu, Keshi Dai, Jav...
DICTA
2003
15 years 8 months ago
A Model Set Based Object Segmentation Method Using Level Set Approach
Abstract. A novel approach for model set based object segmentation is described. The proposed method enables the using of a model set to guide the object segmentation. The object s...
Xun Wang, Zhigang Peng, Feng Gao, William G. Wee
ICCV
2009
IEEE
16 years 11 months ago
Learning Pedestrian Dynamics from the Real World
In this paper we describe a method to learn parameters which govern pedestrian motion by observing video data. Our learning framework is based on variational mode learning and a...
Paul Scovanner, Marshall Tappen
WSC
2000
15 years 8 months ago
Simulation from non-standard distributions using envelope methods
This paper considers the development of envelope methods as a tool for simulation. Envelope methods are based on the construction of simple envelopes to functions. The proposed en...
Michael J. Evans, Tim B. Swartz