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A trajectory-based computational model for optical flow estimation

A new computational model for optical flow estimation is proposed. The proposed model utilizes trajectory information present in a multiframe spatio-temporal volume. Optical flow estimation is formulated as an optimization problem. The solution to this optimization problem yields a velocity field corresponding to smoothest and shortest trajectories of constant intensity points within the spatio-temporal volume. The approach is motivated by principles of inertia of motion and least action in physics and vision psychology. An analogy between a trajectory and a "thin wire" is discussed. A simple mechanism for handling trajectory discontinuities is also incorporated. The optimization problem is solved by stochastic relaxation techniques. Some experimental results and performance comparisons with two existing optical flow estimation techniques are presented to demonstrate the effectiveness of the proposed approach. >