A non-cooperative long-range biometric image tracking and recognition (BITAR) method for maritime surveillance

Xiaokun Li; Genshe Chen; Erik Blasch; Harold H. Szu; Thomas McKenna

doi:10.1117/12.777443

3 April 2008 A non-cooperative long-range biometric image tracking and recognition (BITAR) method for maritime surveillance

Xiaokun Li, Genshe Chen, Erik Blasch, Harold H. Szu, Thomas McKenna

Author Affiliations +

Proceedings Volume 6979, Independent Component Analyses, Wavelets, Unsupervised Nano-Biomimetic Sensors, and Neural Networks VI; 697905 (2008) https://doi.org/10.1117/12.777443
Event: SPIE Defense and Security Symposium, 2008, Orlando, Florida, United States

Abstract

To address the challenges on non-cooperative long-distance human authentication, identification, and verification; we propose an innovative scheme for developing a robust and automatic long-range biometric recognition system by combining face recognition and iris recognition of non-cooperative individuals in 24/7 operations. The system consists of three cameras. One is a wide field of view (WFOV) CCD video camera with InfraRed (IR) filter and powerful IR illuminators for human scan in a wide area and from a long distance. The other two cameras are high resolution video cameras with narrow field of view (NFOV) and IR filter & illuminators, mounted on a pan-tilt-unit (PTU) to capture the frontal view of human face and iris respectively. The WFOV detects the person and the NFOV cameras extract details for person identification. Once the frontal view shots are captured by the NFOV cameras, the face/iris models will be extracted by applying the state-of-the-art face/iris recognizers. In addition, a multimodality fusion approach integrates the face and iris recognition results to improve the overall recognition performance.

Citation Download Citation

Xiaokun Li, Genshe Chen, Erik Blasch, Harold H. Szu, and Thomas McKenna "A non-cooperative long-range biometric image tracking and recognition (BITAR) method for maritime surveillance", Proc. SPIE 6979, Independent Component Analyses, Wavelets, Unsupervised Nano-Biomimetic Sensors, and Neural Networks VI, 697905 (3 April 2008); https://doi.org/10.1117/12.777443

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