SCface --- surveillance cameras face database
Multimedia Tools and Applications
An integrated framework for biometrics security
iUBICOM'10 Proceedings of the 5th international conference on Ubiquitous and Collaborative Computing
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Although automatic identity inference based on faces has shown success when using high quality images, for CCTV based images it is hard to attain similar levels of performance. Furthermore, compared to recognition based on static images, relatively few studies have been done for video based face recognition. In this paper, we present an empirical analysis and comparison of face recognition usinghigh quality and CCTV images in several important aspects: image quality (including resolution, noise, blurring and interlacing) as well as geometric transformations (such as translations, rotations and scale changes). The resultsshow that holistic face recognition can be tolerant to image quality degradation but can also be highly influenced by geometric transformations. In addition, we show that camera intrinsics have much influence – when using different camerasfor collecting gallery and probe images the recognition rate is considerably reduced. We also show that the classification performance can be considerably improved by straightforward averaging of consecutive face imagesfrom a CCTV video sequence.