<title>3D wavelet analysis of eye movements</title>

Abstract

Awareness of the viewer's gaze position in a virtual environment can lead to significant savings in scene processing in fine detail information is presented 'just in time' only at locations corresponding to the participant's gaze, i.e., in a gaze-continent manner. In the development of a gaze-continent manner. In the development of a gaze- contingent system, a model of eye movements is necessary for the exploration of vision and its underlying visual stimuli. The need here is to confidently classify eye movements within natural human viewing patterns. Assuming eye movements composed of dynamic fixations denote overt locations of visual attention, localization of these features is crucial to a gaze-contingent analysis and synthesis of visual information. Due to its simplicity and ease of implementation, a particularly attractive strategy for eye movement modeling involves linear time-invariant (LTI) filtering. In this paper, a conceptual piecewise auto- regressive integrated moving average (PARIMA) model of conjugate eye movements is proposed. The PARIMA model is a piecewise-LTI representation of stochastic signals. The analytical framework of the PARIMA model features a wavelet- based strategy for eye movement segmentation. An off-line video frame-based 3D wavelet analysis technique is proposed for classification of eye movements into smooth pursuits, fixations, and saccades.