Abstract:
Current face recognition systems make extensive use of
class-wise disparate features drawn from faces in order to
achieve state-of-the-art performances. However, there exists
a multitude of information in a given image that is filtered
out due to the current systems being restricted to focusing
entirely on a face. This information prominently includes
co-occurrence of certain individuals together, an individual’s
gait or frequently visited locations.
We have designed a system to utilize such context-based information
as an additional biometric score which is fused
with the score obtained by state-of-the-art recognition systems
to theoretically improve the performance of our vanilla
recognition systems.