The authors present an approach to identify non-cooperative individuals at a distance from a sequence of images using 3D face models.
Most biometric features (such as fingerprints, hand shape, iris or retinal scans) require cooperative subjects in close proximity to the biometric system. We process images acquired with an ultra-high resolution video camera, infer the location of the subjects' head, use this information to crop the region of interest, build a 3D face model, and use this 3D model to perform biometric identification. To build the 3D model, we use an image sequence, as natural head and body motion provides enough viewpoint variation to perform stereo-motion for 3D face reconstruction. Experiments using a 3D matching engine suggest the feasibility of proposed approach for recognition against 3D galleries. (Publisher abstract provided)
Downloads
Similar Publications
- A Multi-Stream Fusion Approach with One-Class Learning for Audio-Visual Deepfake Detection
- Analyzing and interpreting deoxyribonucleic acid from multiple donors using a forensically relevant single-cell strategy
- Learning from Our Casework: The Forensic Anthropology Database for Assessing Methods Accuracy