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Extended Kalman filter (EKF -based objEKF -basedng methobjectproposed in [12].

As explained in Section 1, the proposed tracking method is grounded on a Bayesian inference framework.

Our tracking method is a combination of HCPF and AAM techniques.

The different phase tracking method is adopted in different fault process.

Quadrilateral or triangle tracking method is selected according to the situation during propagation.

The stochastic Lagrangian Particle Tracking method is used to simulate the flow of coal particles.

This in situ particle tracking method is minimally invasive and permits real time measurements.

A basic pitch tracking method is introduced in order to favor smooth transitions of l ̃ ( c ′ ( t ) ).

In this section, the result of the proposed tracking method is compared with simple PF alone and AAM tracking.

The time-dependent dynamic tracking method is proposed to monitor a moving object in the field space.

The resulting meshless front tracking method is tested on sample solidification problems in one and two dimensions.