Deriving an appropriate baseline for describing fixation behaviour

- Measures are obtained for four descriptions of central fixation bias in scene viewing.
- An anisotropic Gaussian performed well over 10 eye-tracking datasets.
- With small sample sizes it delivered better classification than subject-fitted methods.

Humans display image-independent viewing biases when inspecting complex scenes. One of the strongest such bias is the central tendency in scene viewing: observers favour making fixations towards the centre of an image, irrespective of its content. Characterising these biases accurately is important for three reasons: (1) they provide a necessary baseline for quantifying the association between visual features in scenes and fixation selection; (2) they provide a benchmark for evaluating models of fixation behaviour when viewing scenes; and (3) they can be included as a component of generative models of eye guidance. In the present study we compare four commonly used approaches to describing image-independent biases and report their ability to describe observed data and correctly classify fixations across 10 eye movement datasets. We propose an anisotropic Gaussian function that can serve as an effective and appropriate baseline for describing image-independent biases without the need to fit functions to individual datasets or subjects.