Line-based face recognition under varying pose

• Published in: IEEE transactions on pattern analysis and machine intelligence Vol. 21; no. 10; pp. 1081 - 1088
• Main Authors: De Vel, O., Aeberhard, S.
• Format: Journal Article
• Language: English
• Published: IEEE 01.10.1999
• Subjects: Algorithms; Authentication; Biometrics; Face detection; Face recognition; Facial; Humans; Image databases; Image representation; Image segmentation; Imaging; Lighting; Planes; Recognition; Solid modeling; Viewing
• ISSN: 0162-8828; 1939-3539
• DOI: 10.1109/34.799912

Much research in human face recognition involves fronto-parallel face images, constrained rotations in and out of the plane, and operates under strict imaging conditions such as controlled illumination and limited facial expressions. Face recognition using multiple views in the viewing sphere is a more difficult task since face rotations out of the imaging plane can introduce occlusion of facial structures. In this paper, we propose a novel image-based face recognition algorithm that uses a set of random rectilinear line segments of 2D face image views as the underlying image representation, together with a nearest-neighbor classifier as the line matching scheme. The combination of 1D line segments exploits the inherent coherence in one or more 2D face image views in the viewing sphere. The algorithm achieves high generalization recognition rates for rotations both in and out of the plane, is robust to scaling, and is computationally efficient. Results show that the classification accuracy of the algorithm is superior compared with benchmark algorithms and is able to recognize test views in quasi-real-time.