Image Moment-based Object Tracking and Shape Estimation for Complex Motions

In this paper, a novel image moment-based model for shape estimation and tracking of an object moving with a complex trajectory is presented. The camera is assumed to be stationary looking at a moving object. Point features inside the object are sampled as measurements. An ellipsoidal approximation of the shape is assumed as a primitive shape. The shape of an ellipse is estimated using a combination of image moments. A dynamic model of image moments derived in our prior work is used along with the point measurements sampled from the object. An UKF-Interacting Multiple Model (UKF - IMM) filter algorithm is developed to estimate the shape of the object (in terms of an ellipse) and track its position and velocity for objects while performing complex maneuvers. A novel likelihood function based on average log-likelihood is derived for the IMM filter. Simulation results of the proposed UKF-IMM algorithm for the novel image moment-based model are presented to estimate the shape of the object (ellipse approximation) moving in a complex trajectory with high maneuvering index.

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