Introduction

This repository contains the MATLAB code and example dataset described in:

Seacrist et al., "A Scalable Method for Characterizing Visual Search Strategies: A Novel Application of Time Series Clustering to Raw Eye-Tracking Data."

Repository Contents

• ClusterData.xlsx – Example eye-tracking dataset (gaze position and vehicle position)
• dclaw.m – Implementation of Dynamic Coordinate Localized Alignment Warping (DCLAW)
• visualsearchstrategy.m – Main script for performing the time series clustering analysis

Intended Workflow

1. Place 'ClusterData.xlsx', 'dclaw.m', and 'visualsearchstrategy.m' into the same working directory.
2. Open visualsearchstrategy.m in MATLAB 2021b or later.
3. Run the following command in the MATLAB command window to recreate Figures 4-7 in manuscript: 'visualsearchstrategy'

The script performs the complete workflow described in the manuscript, including dissimilarity matrix generation, clustering (k-medoids), and iterative refinement (outlier removal and sub-clustering), and generate figures corresponding to Figures 4–7 in the manuscript.

Notes

The Within-Cluster Sum of Squares (WCSS) and Silhouette Score lines that are combined in Figures 4, 6, and 7 in the manuscript will appear as separate MATLAB figures.