Tracking objects using Gabor filters

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Presentation transcript:

Tracking objects using Gabor filters Mark de Greef, Sjoerd Kerkstra, Roeland Weve Supervisor: Theo Gevers

Tracking objects using Gabor filters Overview Introduction Color spaces Feature selection and mean shift Demonstration Conclusion Tracking objects using Gabor filters

Tracking objects using Gabor filters Introduction Goal: investigate the use of texture in tracking. Trackers often use color features (like RGB) Color features are not sufficient for tracking in some cases We use texture information as a basis for tracking Our tracker is based on the on-line feature selection framework. Tracking objects using Gabor filters

Tracking objects using Gabor filters Color spaces RGB rgb HSV Intensity Tracking objects using Gabor filters

Tracking objects using Gabor filters Captures localized frequency information Biologically motivated Tracking objects using Gabor filters

Tracking objects using Gabor filters 1D Gabor * = Tracking objects using Gabor filters

Tracking objects using Gabor filters 2D Log-Gabor * = Tracking objects using Gabor filters

Inverse Fourier transform IFFT -> Tracking objects using Gabor filters

Tracking objects using Gabor filters Feature selection 1D histograms Background/object separation Tracking objects using Gabor filters

Tracking objects using Gabor filters Mean shift tracking Probability density of target model and target candidate Try to minimize distance between probability densities Tracking objects using Gabor filters

Tracking objects using Gabor filters Demonstration Tracking objects using Gabor filters

Tracking without log-Gabor

Tracking without log-Gabor

Tracking a grid ball

Tracking using log-Gabor Tracking objects using Gabor filters

Tracking objects using Gabor filters Tracking a leaf Tracking objects using Gabor filters

Tracking objects using Gabor filters Tracking without log-Gabor Tracking objects using Gabor filters

Tracking a leaf

Tracking objects using Gabor filters Tracking with log-Gabor Tracking objects using Gabor filters

Tracking objects using Gabor filters Tracking a soccer ball Tracking objects using Gabor filters

Tracking without log-Gabor Tracking objects using Gabor filters

Tracking objects using Gabor filters Tracking a soccer ball Tracking objects using Gabor filters

Tracking with log-Gabor Tracking objects using Gabor filters

Tracking objects using Gabor filters Problems High wavelength log-Gabor filters A frame in the soccer game movie Tracking objects using Gabor filters

Problems High wavelength filters pollute feature selection Solved by limiting wavelength of log-Gabor filter to 2*min(h,w)

Tracking objects using Gabor filters Conclusion Log-Gabor filters make tracking possible in situations where color features do not Problems with large wavelengths can be avoided Addition of log-Gabor features to color features does not degrade tracking performance Tracking objects using Gabor filters

Tracking objects using Gabor filters Questions? Tracking objects using Gabor filters