Curvelet transform-based technique for tracking of moving objects

Abstract

This study provides an object tracking method in video sequences, which is based on curvelet transform. The wavelet transform has been widely used for object tracking purpose, but it cannot well describe curve discontinuities. We have used curvelet transform for tracking. Tracking is done using energy of curvelet coefficients in sequence of frames. The proposed method is simple and does not rely on any other parameter except curvelet coefficients. Compared with a number of schemes like Kalman filter, particle filter, Bayesian methods, template model, corrected background weighted histogram, joint colour texture histogram and covariance-based tracking methods, the proposed method extracts effectively the features in target region, which characterise better and represent more robustly the target. The experimental results validate that the proposed method improves greatly the tracking accuracy and efficiency than traditional methods.