From Points to Faces: An automotive lidar-based face recognition system

From Points to Faces: An automotive lidar-based face recognition system

Humblet Vertongen, Marie (TU Delft Mechanical, Maritime and Materials Engineering)

Caesar, H.C. (mentor)
Peternel, L. (graduation committee)
Zhang, X. (graduation committee)

Delft University of Technology

Mechanical Engineering | Vehicle Engineering | Cognitive Robotics

2023-09-13

Face recognition using lidar presents challenges arising from high dimensionality and data sparsity, especially at longer distances. This paper proposes a novel approach for face recognition via automotive lidar. The approach leverages a combination of deep learning and point cloud processing techniques. After identification of the facial point clouds, an alpha-shaped convex hull is employed for regional linearization, resulting in the creation of a depth image. This depth image is then fed to a convolutional neural network architecture, BasicNet, specifically trained for face recognition. The approach is evaluated on a dataset comprising 52 individuals acquired using two lidar sensors with different point densities. The individuals walked at distances ranging from 5 to 18 meters from the sensors. The approach achieves interesting results on this challenging dataset, thereby challenging the notion that lidar sensors are privacy-preserving.

Face Recognition
Automotive lidar
Privacy

http://resolver.tudelft.nl/uuid:9c898ec1-2850-425b-8501-888f0535c5a8

52.00096, 4.37142

Student theses

master thesis

© 2023 Marie Humblet Vertongen