Project detail

Controlo Acessos @ Convento Cristo

Computer vision system for counting and tracking people in the Charola of the Convent of Christ using YOLO and DeepSort.

Applied research BSc final projectMSc thesisComputer vision 2023–Ongoing Ongoing
Controlo Acessos @ Convento Cristo screenshot

Overview

The Controlo de Acessos @ Convento Cristo project consists of a computer vision system to count and track people entering and exiting the Charola of the Convent of Christ in Tomar. The system uses real-time video feeds to support visitor management at a UNESCO World Heritage monument.

Approach

The system combines YOLO for real-time object detection with multi-object tracking algorithms such as DeepSort. This pipeline detects people in each video frame, tracks individuals across frames, and counts entries and exits by monitoring trajectories across defined boundary lines.

Background

Gonçalo Sousa initiated the project as his MSc thesis, integrating YOLOv5 and DeepSORT into an early research prototype and building a Flask-based web dashboard for visitor reporting. His work validated the feasibility of ML-based visitor counting at the site.

Sofia Vendor is now continuing the project as her BSc final project. Her focus is on revamping the solution with newer YOLO models, refining the tracking pipeline, and taking the system towards an in-situ prototype for real-conditions testing at the Convent of Christ.

Technologies

Python YOLO DeepSort OpenCV Docker

Outputs

Sousa, G. (2024). Securing Heritage Spaces: A Machine Learning Powered Dashboard for Real-time Visitor Management [Master's thesis]. Instituto Politécnico de Tomar.