Biometric Recognition In-The-Wild
A special issue of Symmetry (ISSN 2073-8994).
Deadline for manuscript submissions: closed (31 May 2016) | Viewed by 7328
Special Issue Editor
Interests: pattern recognition; computer vision; biometrics; visual surveillance
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The domain of Pattern Recognition has been attracting substantial research efforts, and is the scope of a large number of active research lines. Among these, biometrics is considered an especially successful case, even though performance is still strongly conditioned by the levels of cooperation demanded to subjects and by the environmental conditions during data-acquisition.
This Special Issue is particularly interested in emerging strategies to perform biometric recognition based on data acquired in wild scenarios, i.e., outdoors, from large distances and without requiring subjects cooperation for data acquisition, which should dramatically decrease the discriminability of the information obtained. The development of such types of recognition systems will broaden the range of domains where biometrics can be used, particularly for forensic/security purposes.
Considering that many problems remain to be solved, and that the proposal of techniques effective in such challenging situations requires vigorous research efforts, we are particularly interested in novel ideas about how to compensate for the adversity of the data/environments to perform accurate biometric recognition.
Topics of interest include, but are not strictly limited to:
- Less controlled/covert data acquisition frameworks
- Detection of regions of interest (landmarks) in real-world data
- Segmentation of biometric traits
- Robust feature encoding / matching
- Multi-biometrics systems: fusion at different levels
- Biometric recognition in surveillance scenarios
- Announcement of challenging biometric data sets
- Ethical issues/concerns about covert biometric recognition systems
- Reaction plans against security incidents raised by automated recognition systems
- Biometric recognition benchmarks for unconstrained data acquisition environments
Dr. Hugo Pedro Proença
Guest Editor
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