Face Annotation at the Macro-scale and the Micro-scale: Tools, Techniques, and Applications in Forensic Identification

• NCJ Number: 243277
• Author(s): Patrick J. Flynn; Anil K. Jain
• Date Published: 2013
• Length: 8 pages
• Grant Number(s): 2009-DN-BX-K231
• Agencies: NIJ-Sponsored
• Publication Type: Report (Study/Research); Report (Grant Sponsored)
• Award: Face Annotation at the Macro-scale and the Micro-scale: Tools, Techniques, and Applications in Forensic Identification

Annotation

This project developed, evaluated, and documented a system for facial verification that uses detected facial-marks rather than holistic or larger scale facial structures.

Abstract

The project developed a robust facial-mark detection method that provides both location and scale information for facial marks. The project has shown the utility of facial marks in face-image retrieval tasks using a large-scale face-image database. The proposed facial-mark matching scheme can be combined with COTS face matcher to improve the overall matching accuracy. The improvements in face matching accuracy are shown both on the general face-image database and the identical-twin face-image database. The project then proposed a conditional filtering scheme in order to reduce the retrieval time on a large-scale face-image database. The study of symbolic query base face-image retrieval showed a great utility for facial marks when query image is not available. The project concludes that although a number cases were found in which facial marks can be used for face-image retrieval tasks, the instability of facial marks is still a major challenge in using facial marks in practice. The instability of facial marks is mainly caused by the low quality of face mug-shot images. The development of a more robust facial-mark detection and representation scheme and establishing a standard practice in face mug-shot image capture that would ensure sufficient quality of image are some of the imminent requirements for extending the use of facial marks. 3 figures