Janus
Intelligence analysts often rely on facial images to assist in establishing the identity of an individual, but too often, just examining the sheer volume of possibly relevant images and videos can be daunting. While biometric tools like automated face recognition could assist analysts in this task, current tools perform best on the well-posed, frontal facial photos taken for identification purposes. IARPA’s Janus program aims to dramatically improve the current performance of face recognition tools by fusing the rich spatial, temporal, and contextual information available from the multiple views captured by today’s “media in the wild”. The program will move beyond largely two-dimensional image matching methods used currently into more model-based matching that fuses all views from whatever video and stills are available. Data volume now becomes an integral part of the solution instead of an oppressive burden.
The program is seeking to fund rigorous, high-quality research which uses innovative and promising approaches drawn from a variety of fields to develop novel representational models capable of encoding the shape, texture, and dynamics of a face. Instead of relying on a “single best frame approach,” these representations must address the challenges of Aging, Pose, Illumination, and Expression (A-PIE) by exploiting all available imagery. Technologies must support analysts working with partial information by addressing the uncertainties which arise when working with possibly incomplete, erroneous, and ambiguous data. The goal of the program is to test and validate techniques which have the potential to significantly improve the performance of biometric recognition in unconstrained imagery, to that end, the program will involve empirical testing of recognition performance across unconstrained videos, camera stills, and scanned photos exhibiting a broad range of real-world imaging conditions.
It is anticipated that successful teams will transcend conventional approaches to biometric recognition by drawing on the multidisciplinary expertise of researchers from the fields of pattern recognition and machine learning; computer vision and image processing; computer graphics and animation; mathematical statistics and modeling; and data visualization and analytics.
Performers (Prime Contractors)
SRI International; Systems & Technology Research; University of Maryland; University of Southern California
Related Program(s)
BESTResearch Area(s)
- Computer vision
- Image processing
- Pattern recognition
- Biometrics
- Facial recognition
- Identity intelligence
- Computer graphics
Related Publications and Websites
The IARPA Janus Benchmark A (IJB-A) is part of the National Institute of Standards and Technology Face Challenges, an ongoing evaluation activity to support the face recognition research community. The IJB-A dataset and performance leaderboard is available here.
To access Janus program-related publications, please visit Google Scholar:
R&D AuthorsRelated Article(s)
- Facial recognition improving at breakneck speeds'
- IARPA-Funded Project Advances Biometrics Intelligence
- Wild Gadgets Fit for a Real-Life James Bond
- Intelligence agency seeks facial recognition upgrade
- 'Soft' biometrics is the new way to monitor people
- Washington frets over 'Minority Report'-style facial recognition technology
- US Intelligence Agency seeks dramatic face recognition improvement
- US intelligence wants to radically advance facial recognition software
- Intelligence researchers seek to make big improvements in biometric facial recognition
- Intel Research Arm Wants to Tap ‘Media in the Wild’ for Facial Recognition
