Paper
4 February 1999 Faceless identification: a model for person identification using the 3D shape and 3D motion as cues
Lena M. Klasen, Haibo Li
Author Affiliations +
Proceedings Volume 3576, Investigation and Forensic Science Technologies; (1999) https://doi.org/10.1117/12.334533
Event: Enabling Technologies for Law Enforcement and Security, 1998, Boston, MA, United States
Abstract
Person identification by using biometric methods based on image sequences, or still images, often requires a controllable and cooperative environment during the image capturing stage. In the forensic case the situation is more likely to be the opposite. In this work we propose a method that makes use of the anthropometry of the human body and human actions as cues for identification. Image sequences from surveillance systems are used, which can be seen as monocular image sequences. A 3D deformable wireframe body model is used as a platform to handle the non-rigid information of the 3D shape and 3D motion of the human body from the image sequence. A recursive method for estimating global motion and local shape variations is presented, using two recursive feedback systems.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Lena M. Klasen and Haibo Li "Faceless identification: a model for person identification using the 3D shape and 3D motion as cues", Proc. SPIE 3576, Investigation and Forensic Science Technologies, (4 February 1999); https://doi.org/10.1117/12.334533
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Cited by 3 scholarly publications.
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KEYWORDS
3D modeling

Motion estimation

Motion models

Cameras

3D image processing

Filtering (signal processing)

Forensic science

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