Tracking of multiple human objects using a Combination of Daubechies complex wavelet transform and Zernike moment

Abstract

The goal of multi object tracking is to find location of the target objects in number of consecutive frames of a video. Tracking of multiple human objects in a scene is one of the challenging problems in computer vision applications due to illumination variation, object occlusion, abrupt motion etc. This paper introduces a new method for multiple human object tracking by exploiting the properties of Daubechies complex wavelet transform and Zernike moment. The proposed method uses combination of Daubechies complex wavelet transform and Zernike moment as a feature of objects. The motivation behind using combination of these two as a feature of object, because shift invariance and better edge representation properties make Daubechies complex wavelet transform suitable for locating object in consecutive frames whereas translation invariant property of Zernike moment is also helpful for correct object identification in consecutive frames. The proposed method is capable to handle full occlusion, partial occlusion, split and object re-enter problems. The experimental results validate the effectiveness and robustness of the proposed method.