IJCB 2011 - Competitions Program



The International Joint Conference on Biometrics (IJCB 11) is a special combination of two major biometrics research conference traditions, the International Conference on Biometrics (ICB) and the Biometrics Theory, Application and Systems (BTAS) conference. The blending of these two conferences for this this one year is through special agreement of the IEEE and IAPR, and should present quite an exciting event for the entire worldwide biometrics research community.

Aiming at promoting and advancing biometric recognition technology, several competitions will be held in the scope of IJCB 11:

- Evaluation of Signature Resistance to Attacks (ESRA 2011). Recent research in the field of Biometrics has shown an increased interest on systems' resistance to attacks. In the online signature modality, verification performance has been evaluated for a long time on databases containing skilled forgeries, which can be of different qualities. This quality can greatly vary depending on the capacity of an impostor to forge a genuine signature, on the difficulty to reproduce such genuine signature, and also on the available information to the impostor about the target genuine signature (dynamic or static information).  In this context, IJCB 2011 Evaluation of Signature Resistance to Attacks (ESRA’2011) aims at assessing the resistance of online signature verification systems to different quality-based categories of skilled forgeries. To this aim, the quality of skilled forgeries is quantified by means of a new measure based on the concept of Personal Entropy relatively to the target genuine signatures. Additional information about this competition can be found at: http://biometrics.it-sudparis.eu/ESRA2011/

- IJCB 2011 Competition on counter measures to 2D facial spoofing attacks. Facial recognition techniques are currently deployed in a wide range of applications for access control, security, law-enforcement and database indexing, to cite a few. As in any other field of Biometrics such as speaker or fingerprint verification, 2-D facial recognition systems are subject to attacks. In direct attacks, potential intruders try and may gain access to classified information by interacting directly with the system input cameras, like a normal user would. Such attempts are commonly referred as "spoofing". For this competition we would like to measure the performance of algorithms that act as a counter-measure to spoofing. You are invited to submit your technique for evaluation. Additional information about this competition can be found at: http://www.tabularasa-euproject.org/evaluations/ijcb-2011-competition-on-counter-measures-to-2d-facial-spoofing-attacks

- Fingerprint Verification Competition.  FVC-onGoing@IJCB11 is a fingerprint verification competition based on the following FVC-onGoing benchmarks: FV-STD-1.0: Fingerprint verification (proprietary templates) on a dataset of fingerprint images acquired in operational conditions using high-quality optical scanners. FV-HARD-1.0: Fingerprint verification (proprietary templates) on a dataset which contains a relevant number of difficult cases (noisy images, distorted impressions, etc.). FMISO-STD-1.0: Fingerprint matching using a standard minutiae-based template format [ISO/IEC 19794-2 (2005)] on a dataset of fingerprint images acquired in operational conditions using high-quality optical scanners. FMISO-HARD-1.0: Fingerprint matching using a standard minutiae-based template format [ISO/IEC 19794-2 (2005)] on a dataset which contains a relevant number of difficult cases (noisy images, distorted impressions, etc.). Submission and evaluation of the algorithms follow the standard FVC-onGoing rules. Additional information about this competition can be found at: https://biolab.csr.unibo.it/fvcongoing/UI/Form/IJCB2011.aspx

- Fingerprint Liveness Detection Competition 2011. A recent issue in the field of security in fingerprint verification (unsupervised especially) is known as “liveness detection”. The standard verification system is coupled with additional hardware or software modules aimed to certify the authenticity of the submitted fingerprints. Whilst hardware-based solutions are the most expensive, software-based ones attempt to measure liveness from characteristics of images themselves by simply applying image processing algorithms. The goal of the competition is to compare different methodologies for software-based fingerprint liveness detection with a common experimental protocol and data set. The ambition of the competition is to become the reference event for academic and industrial research. The competition is not defined as an official system for quality certification of the proposed solutions, but may impact the state of the art in this crucial field, with reference to the general problem of security in biometric systems. Additional information about this competition can be found at: http://people.clarkson.edu/projects/biosal/fingerprint/index.php

- Face Detection on Hard Datasets Competition 2011. Facial detection algorithms are deployed in a wide range of application. But when presented a challenging image; distance, low light, etc, they often fails or return false positives. This competition will measure the accuracy of face detection algorithms when presented with a dataset of hard images. The dataset is a subset of PIE which has been rephotographed under a variety of challenging conditions.. Additional information about this competition can be found at: http://vast.uccs.edu/FDHD

- Questionable Observer Detection Competition (QuODC) 2011. Given a set of videos capturing crowds watching a series of events, determine which individuals appear in more than v videos.  The individuals that appear in more than v videos are called questionable observers, whereas people that appear in at most v videos are called casual observers.  For this competition, v is set to 1.  In other words, the objective posed here is to distinguish the questionable observers that appear in more than one video from the casual observers that appear in exactly one video without the benefit of an existing database of faces with known labels. The lack of labeling information means that this is a face clustering problem as opposed to a traditional face recognition problem.  First, faces must be detected or tracked in the videos, and then the faces must be grouped together to form a clustering.  As depicted in the diagram below, clusters that contain patterns from more than a single video should be reported as questionable observer clusters. Additional information about this competition can be found at: http://www.cse.nd.edu/IJCB_11/QuODCompetition.htm

Each competition results and summary will be presented and discussed in IJCB 11 and the best participants will be invited to present their approach and publish it in the conference proceedings.