Population Codes for Orientation Estimation

Niklas Lüdtke, Richard C. Wilson, Edwin R. Hancock

Abstract: Population coding has become an essential paradigm in cognitive neuroscience over the past decade and is increasingly studied within the neural network community. We investigate the use of population vector decoding for local edge orientation estimation from a discrete set of Gabor filters. Vectorial combination of the broadly tuned filter outputs yields a resultant population vector, which gives a precise and robust estimate of the local contour orientation. We present results on the accuracy and robustness of orientation measurement.