Supervised Semantic Object Segmentation and Tracking via EM-based Estimation of Mixture Density Parameters.
Noel E. O'ConnorSeán MarlowPublished in: NMBIA (1998)
Keyphrases
- expectation maximization
- maximum likelihood estimation
- parameter estimation
- em algorithm
- mixture model
- maximum likelihood
- unsupervised learning
- log likelihood function
- gaussian mixture
- maximum likelihood estimates
- likelihood function
- expectation maximisation
- probabilistic model
- density estimation
- gaussian mixture model
- density distribution
- density function
- mixture of gaussians
- machine learning
- estimation process
- probability density
- domain specific
- image segmentation
- generative model
- exponential family
- maximum likelihood estimator
- object segmentation and tracking
- supervised learning
- semi supervised
- estimation algorithm
- probability density function
- bayesian framework
- parameter space
- maximum a posteriori
- closed form
- semantic information
- active contours
- dimensionality reduction
- estimate the model parameters
- hidden markov models