A Real-World Dataset for Abnormal Behavior Detection in Turnstile Gates

This dataset contains real-world surveillance data collected from turnstile gate environments for abnormal behavior detection. The dataset includes:- RGB video sequences captured from real operational turnstile gates- Extracted image frames- Various human behaviors, including normal passage and abnormal actions (e.g., tailgating, unauthorized entry, loitering) The data was collected under real-world conditions and is intended for research in:- Computer vision- Video anomaly detection- Human behavior analysis- Smart access control systems This dataset was used in the study:"A TimeSformer-Based Approach with LSTM and Attention for Detecting Abnormal Behaviors in Turnstile Gates"