A Parametric Spectral Model for Texture-Based Salience
Kasim Terzić, Sai A. Krishna, J. M. H. du Buf · Lecture notes in computer science · 2015
We present a novel saliency mechanism based on texture. Local texture at each pixel is characterised by the 2D spectrum obtained from oriented Gabor filters. We then apply a parametric model and describe the texture at each pixel by a combination of two 1D Gaussian approximations. This results in a simple model which consists of only four parameters. These four parameters are then used as feature channels and standard Difference-of-Gaussian blob detection is applied in order to detect salient areas in the image, similar to the Itti and Koch model. Finally, a diffusion process is used to sharpen the resulting regions. Evaluation on a large saliency dataset shows a significant improvement of our method over the baseline Itti and Koch model. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.