A real-time probabilistic channel flood-forecasting model based on the Bayesian particle filter approach.
Xingya XuXuesong ZhangHongwei FangRuixun LaiYuefeng ZhangLei HuangXiaobo LiuPublished in: Environ. Model. Softw. (2017)
Keyphrases
- particle filter
- real time
- bayesian inference
- particle filtering
- rainfall runoff
- visual tracking
- proposal distribution
- sequential monte carlo
- object tracking
- state estimation
- bayesian networks
- kalman filter
- posterior probability
- motion model
- appearance model
- monte carlo
- state space
- importance sampling
- likelihood function
- markov chain monte carlo
- observation model
- robust visual tracking
- probabilistic model
- multiple hypotheses
- robust tracking
- bayesian filtering
- data association
- target tracking
- multiple objects
- multiple object tracking
- multiple hypothesis
- mean shift
- generative model
- abrupt motion
- rao blackwellized particle filter
- simultaneous localization and mapping
- face tracking
- moving target
- image sequences
- learning algorithm
- tracking accuracy
- extended kalman filter
- tracking framework
- real environment
- kalman filtering
- posterior distribution
- computer vision