Object tracking using the Gabor wavelet transform and the golden section algorithm

This paper presents an object tracking method for object-based video processing which uses a two-dimensional (2-D) Gabor wavelet transform (GWT) and a 2-D golden section algorithm. An object in the current frame is modeled by local features from a number of the selected feature points, and the global placement of these feature points. The feature points are stochastically selected based on the energy of their GWT coefficients. Points with higher energy have a higher probability of being selected since they are visually more important. The amplitudes of the GWT coefficients of a feature point are then used as the local feature. This takes advantage of the characteristics of Gabor wavelets which are highly localized in both the time and the frequency domains. The global placement of the feature points is determined by a 2-D mesh whose feature is the area of the triangles formed by the feature points. In this way, a local feature is represented by a GWT coefficient amplitude vector, and a...

• Type: Journal
• Year: 2002
• Where: TMM
• Authors: Chao He, Yuan F. Zheng, Stanley C. Ahalt
• Keywords: Feature Points, Gwt Coefficient, Local Features, TMM 2002