Eye Tracking Data for Building Facade Inspection by Ten Participants

Ten participants in their mid-twenties to thirties performed building facade inspections while wearing Tobii Pro Glasses 3. The dataset captures eye-tracking data from two structures to understand inspector reasoning for damage assessment. Muhammad Rakeh Saleem from Pennsylvania State University collected the data for a preliminary study, with post-processing done using Tobii Pro Lab software.

Use Cases

• Modeling visual attention patterns based on recorded eye-tracking data.
• Analyzing inspector sense-making processes for structural damage assessment.
• Training algorithms for automated damage detection by learning from human gaze behavior.
• Studying human factors and cognitive workload during visual inspection tasks.

Strengths

• Data was collected from ten participants, providing multiple perspectives.
• Uses a specific, professional-grade data collection tool: Tobii Pro Glasses 3 wearable eye-tracking system.
• Focuses on a defined task: inspection of two building facades.

Limitations

• Row count and dataset scale are unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The participant pool is limited to students in a specific age range, which may not represent all inspectors.

Provenance

Source

Pennsylvania State University

Collection Method

Collected using Tobii Pro Glasses 3 wearable eye-tracking system, post-processed with Tobii Pro Lab software.