Eye movement analysis in simple visual tasks

Abstract

The small eye movements in the process of fixation on an image element give us knowledge about the human visual information perception. An indepth analysis of these movements can reveal the influence of personality, mood and mental state of the examined subject on the process of perception. The modern eye tracking technology provides us with the necessary technical means to study these movements. Nevertheless, still a lot of problems remains open. In the present paper two approaches for noise cancellation in the eye-tracker signal and two approaches for microsaccade detection are proposed. The analysis of the obtained results can be a good starting point for interpretation by neurobiologists about the causes of different types of movement and their dependence on the individuality of the observed person and the specific mental and physical condition.

Can Microsaccades Be Used for Biometrics?

“…The second algorithm—Kalman filtering—is built on a 2D model of eye movement, containing a state vector (velocity and position of the eye in horizontal and vertical directions/axes) and a transition matrix [ 48 ], which are describing the physical model of eye movement. The error covariance matrices of the state and measurement vectors are calculated according to expressions in [ 20 ] or replaced with the values estimated in [ 47 ]. The noise filtration procedure ends with power supply harmonics rejection (at 50 Hz and 100 Hz; others were already removed with previous filtering).…”

“…The second step consists of microsaccade detection. Three different algorithms were proposed in [ 20 ]. Two of them could be regarded as enhanced versions of the well-known classical Engbert and Kliegl algorithm [ 49 , 50 ] with a different window size and adaptive threshold.…”

“…Here, a short explanation of the preprocessing steps for the ET data is given and shown schematically in Figure 1 . A detailed description can be found in [ 20 ].…”

“…Another paper suggested that fixation-mode eye drift is related to the encoding and processing of visual information in space and time [ 18 ]. Recently, the authors of [ 19 , 20 ] showed that drift is inversely correlated with the head/body movements with some delay in time. This means that the eye drift’s inverse correspondence to these movements gives us information about the velocities and amplitudes of body and head micro movements.…”

Microsaccade Selectivity as Discriminative Feature for Object Decoding

“…They aid in continuously sampling our visual environment, thus enhancing our interpretation of the environment. This assistance in visual scene interpretation enables a deeper understanding of the environment, recognizing faces, and supporting various visually demanding tasks (Chen et al, 2022; Alexiev and Vakarelsky, 2022). Meanwhile, smooth pursuit movements enable the eyes to follow moving objects smoothly, ensuring consistent and precise visual tracking (Barnes, 2008; Souto and Kerzel, 2021; Parisot et al, 2021).…”