Assessment of time dependency in face recognition: an initial study

Abstract. As face recognition research matures and products are deployed, the performance of such systems is being scrutinized by many constituencies. Performance factors of strong practical interest include the elapsed time between a subject’s enrollment and subsequent acquisition of an unidentified face image, and the number of images of each subject available. In this paper, a long-term image acquisition project currently underway is described and data from the pilot study is examined. Experimental results suggest that (a) recognition performance is substantially poorer when unknown images are acquired on a different day from the enrolled images, (b) degradation in performance does n o t follow a simple predictable pattern with time between known and unknown image acquisition, and (c) performance figures quoted in the literature based on known and unknown image sets acquired on the same day may have little practical value. 1

Cross-channel histogram equalisation for colour face recognition

Changes in illumination conditions will alter the appearance of digital images that will in turn have a detrimental effect on face recognition. To overcome the problem, histogram equalisation has already been applied to grey world face recognition and extended to colour object recognition by independently processing the three colour channels. This paper furthers this work by introducing a new technique, cross-channel histogram equalisation, and reports upon its application to colour face recognition under different illumination conditions. Based on the experimental tests, our approach has been shown to outperform other efforts on histogram equalisation for normalisation. Finally we give our conclusions and discuss future wor