Supplementary Material for the Paper "Quantitative Evaluation of Comparative Visualization Methods for Change Identification in Multi-Temporal Point Clouds"

This folder contains the data and code related to the user study presented in our paper "Quantitative Evaluation of Comparative Visualization Methods for Change Identification in Multi-Temporal Point Clouds" (currently under review). Data datasets.zip: test datasets and ground truth annotations used in the study study_raw_results.zip: participant annotations and screenshots data_time.csv: task completion times per participant data_accuracy.csv: results of comparing the participant annotations against the ground truth per task task_to_dataset.json: mapping from local task indices per participant to the dataset used in each task task_to_method.json: mapping from local task indices per participant to the visualization method used in each task Code Python scripts for postprocessing the data and performing the statistical tests are provided.requirements.txt lists the required Python packages for running the scripts. First, run the postprocess_results scripts inside this folder. This creates a folder containing Q-Q plots and CSV files with the postprocessed study results.Then, run the statistical_test scripts to perform the statistical evaluation.