Visual object tracking using Fourier domain phase information

In this article, phase of the Fourier transform (FT), which has observed to be a crucial component in image representation, is utilized for visual target tracking. The main aim proposed scheme reduce computational complexity cross-correlation-based matching frameworks. Normalized cross-correlation (NCC) function-based object tracker converted minimization problem under following assumption: tracking applications, if frame rate high, moving can considered have translational shifts domain small time window. Since framework works domain, space are variations due “translational invariance” property FT. algorithm estimates spatial position based on information region. uses \(\ell _1\)-norm and provides computationally efficient solution problem. Experimental studies indicate that phase-based technique obtain comparable results with baseline algorithms more complex.