The NIST HumanID Evaluation Framework
نویسندگان
چکیده
The NIST HumanID Evaluation Framework, or HEF, is an effort to design, implement, and deploy standards for the robust and complete documentation of the biometric system evaluation process. The HEF is leverages contemporary technologies, specifically XML, for the formal description of biometric tests. The HEF was used to facilitate the administration of the Face Recognition Vendor Test (FRVT) 2002. Unlike FRVT 2000 or the FERET 1996 evaluations, FRVT 2002 used a large number (over 100,000) of both still and video facial imagery, warranting the development of a more sophisticated and regular means of describing data presented to the participants. The HEF is one component in NIST’s ongoing effort to address the need in the biometrics community for a common evaluation framework.
منابع مشابه
NIST Biometrics Evaluations and Developments
This paper presents an R&D framework used by the National Institute of Standards and Technology (NIST) for biometric technology testing and evaluation. The focus of this paper is on fingerprint-based verification and identification. Since 9-11 the NIST Image Group has been mandated by Congress to run a program for biometric technology assessment and biometric systems certification. Four essenti...
متن کاملGait Shape Estimation for Identification
A method is presented for identifying individuals by shape, given a sequence of noisy silhouettes segmented from video. A spectral partitioning framework is used to cluster similar poses and automatically extract gait shapes. The method uses a variance-weighted similarity metric to induce clusters that cover disparate stages in the gait cycle. This technique is applied to the HumanID Gait Chall...
متن کاملSUT Submission for NIST 2016 Speaker Recognition Evaluation: Description and Analysis
In this paper, the most recent Sharif University of Technology (SUT) speaker recognition system developed for NIST 2016 Speaker Recognition Evaluation (SRE) is described. The major challenge in this evaluation is the language mismatch between training and evaluation data. The submission is related to the fixed condition of NIST SRE 2016 and features a full description of the database and the sy...
متن کاملThe Nist 2004 Spring Rich Transcription Evaluation: Two-axis Merging Strategy in the Context of Multiple Distant Microphone Based Meeting Speaker Segmentation
This paper presents the ELISA speaker segmentation approach applied on multiple audio channel meeting recordings in the framework of NIST RT’04s meeting (spring) evaluation campaign. As done for BN data speaker segmentation, the ELISA “meeting” system involves two speaker segmentation systems developed individually by the CLIPS and LIA laboratories. The main originality consists in a “two-axis”...
متن کاملTechnical Improvements of the E-HMM Based Speaker Diarization System for Meeting Records
This paper is concerned with the speaker diarization task in the specific context of the meeting room recordings. Firstly, different technical improvements of an E-HMM based system are proposed and evaluated in the framework of the NIST RT’06S evaluation campaign. Related experiments show an absolute gain of 6.4% overall speaker diarization error rate (DER) and 12.9% on the development and eval...
متن کامل