5 topics (In about 10 lectures)：
Topic 1 Estimating 2D and 3D Motion from Image Sequences
(Motion field and optical flow; Aperture problem; Locas-Kanade’s method; Dense flow; Horn-Schunck’s method; Parametric flow; Robust flow computation; Flow-based motion segmentation; Generalized PCA; Flow-based 3D motion analysis; Direct methods; Ego motion; Parallax; Multiple view motion analysis; etc.)
Topic 2 Differential Motion Analysis
(Formulation; Singularities; Kernel-based methods; Mean-shift tracking; Support vector machine tracking; Multiple kernel tracking; Multiple collaborative kernel tracking, etc.)
Topic 3 Sequential Monte Carlo Motion Analysis
(Sequential Monte Carlo; Particle filtering; Factored sampling; Importance sampling; Markov chain Monte Carlo; Metropolis-Hastings; etc.)
Topic 4 Capturing Articulated Motion
(Twists and exponential maps; Markov random field; Markov network; Bayesian inference; Belief propagation; non-parametric BP; Probabilistic variational analysis; Mean-field variation; Mean-field Monte Carlo; Variational maximum a posteriori; etc.)
Topic 5 Tracking Multiple Targets
(Coalescence; Occlusions; Data association; Joint state space; Probabilistic data association filtering; Joint probabilistic data association filtering; Decentralized tracking; Tracking a variable number of targets; MCMC tracking; RJ-MCMC tracking; etc.) |