Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Cathy L. Schott

dblp:97/7992 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
0since 2021 · last 2010
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
1 paper
Biometric security · 100%
Artificial intelligence
1 paper
Face, body and person analysis · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computer vision › Face, body and person analysis
face recognition
0.112010
FRVT 2006 and ICE 2006 Large-Scale Experimental Results · IEEE Trans. Pattern Anal. Mach. Intell. 2010
Biometric security
iris recognition
0.112010
FRVT 2006 and ICE 2006 Large-Scale Experimental Results · IEEE Trans. Pattern Anal. Mach. Intell. 2010
Biometric security › iris recognition
iris recognition evaluation
0.112010
FRVT 2006 and ICE 2006 Large-Scale Experimental Results · IEEE Trans. Pattern Anal. Mach. Intell. 2010
Computer vision › Face, body and person analysis › face recognition
3d face recognition
0.012010
FRVT 2006 and ICE 2006 Large-Scale Experimental Results · IEEE Trans. Pattern Anal. Mach. Intell. 2010
YearPublicationVenuePosition
2010 FRVT 2006 and ICE 2006 Large-Scale Experimental Results
abstract
This paper describes the large-scale experimental results from the Face Recognition Vendor Test (FRVT) 2006 and the Iris Challenge Evaluation (ICE) 2006. The FRVT 2006 looked at recognition from high-resolution still frontal face images and 3D face images, and measured performance for still frontal face images taken under controlled and uncontrolled illumination. The ICE 2006 evaluation reported verification performance for both left and right irises. The images in the ICE 2006 intentionally represent a broader range of quality than the ICE 2006 sensor would normally acquire. This includes images that did not pass the quality control software embedded in the sensor. The FRVT 2006 results from controlled still and 3D images document at least an order-of-magnitude improvement in recognition performance over the FRVT 2002. The FRVT 2006 and the ICE 2006 compared recognition performance from high-resolution still frontal face images, 3D face images, and the single-iris images. On the FRVT 2006 and the ICE 2006 data sets, recognition performance was comparable for high-resolution frontal face, 3D face, and the iris images. In an experiment comparing human and algorithms on matching face identity across changes in illumination on frontal face images, the best performing algorithms were more accurate than humans on unfamiliar faces.
P. Jonathon Phillips, W. Todd Scruggs, Alice J. O'Toole, Patrick J. Flynn, Kevin W. Bowyer, Cathy L. Schott, Matthew Sharpe
IEEE Trans. Pattern Anal. Mach. Intell.6