About this role
Purpose The internship aim s to advanc e the " Freeflow" technology , focusing on the detection and tracking part . Freeflow moves beyond traditional biometric gates—which require passengers to stop for facial, fingerprint, or iris scanning— by leverag ing advanced video analytics to identify individuals seamlessly as they move. T h is creates a frictionless user experience by eliminating physical barriers. We want to design a lightweight neural network that, from a single calibrated camera, detects (i.e., predicts its 2D image position) every pedestrian head in a possibly dense scene and predicts for each head its metric depth.
- Each detection is then lifted to a 3D point . The 3D points coming from several synchronized cameras are associated in 3 D and fed to a 3D tracker . The final goal is to achieve more robust, 3D - aware tracking . Key Missions Analyzing and understanding the current crowd localization model architecture and performance.
- Conducting experiments to evaluate tracking precision.
- Collaborating with a team of researchers to contribute to the overall project goals.
- Documenting findings and presenting results.
- Profile & Other Information Education Final-year engineering student at a leading engineering school, or a second-year Master's student (M2) specializing in computer vision, image processing, or deep learning.
- Technical Skills Strong knowledge of computer vision and deep learning.
- Proficiency in Python, OpenCV, and PyTorch.
- Solid background in data analysis and software development.
- Interpersonal Skills and Languages Proficiency in written and spoken English, including the ability to read and understand scientific papers.
- Curious, proactive, and self-motivated, with the ability to work independently.
- Results-driven, with a strong problem-solving mindset.
- Excellent communication skills, with the ability to present ideas clearly and persuasively.
- Strong interest in contributing to the full lifecycle of an algorithm, from design and implementation to integration, testing, and optimization.
Location: La Défense, Courbevoie, France Duration: 6 months Expected Start Date: Approximately March 2027