Accurate pose estimation for forensic identification

Gert Merckx; Jeroen Hermans; Dirk Vandermeulen

doi:10.1117/12.849913

14 April 2010 Accurate pose estimation for forensic identification

Gert Merckx, Jeroen Hermans, Dirk Vandermeulen

Proceedings Volume 7667, Biometric Technology for Human Identification VII; 76670S (2010) https://doi.org/10.1117/12.849913
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States

Abstract

In forensic authentication, one aims to identify the perpetrator among a series of suspects or distractors. A fundamental problem in any recognition system that aims for identification of subjects in a natural scene is the lack of constrains on viewing and imaging conditions. In forensic applications, identification proves even more challenging, since most surveillance footage is of abysmal quality. In this context, robust methods for pose estimation are paramount. In this paper we will therefore present a new pose estimation strategy for very low quality footage. Our approach uses 3D-2D registration of a textured 3D face model with the surveillance image to obtain accurate far field pose alignment. Starting from an inaccurate initial estimate, the technique uses novel similarity measures based on the monogenic signal to guide a pose optimization process. We will illustrate the descriptive strength of the introduced similarity measures by using them directly as a recognition metric. Through validation, using both real and synthetic surveillance footage, our pose estimation method is shown to be accurate, and robust to lighting changes and image degradation.

Citation Download Citation

Gert Merckx, Jeroen Hermans, and Dirk Vandermeulen "Accurate pose estimation for forensic identification", Proc. SPIE 7667, Biometric Technology for Human Identification VII, 76670S (14 April 2010); https://doi.org/10.1117/12.849913

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