In this paper, we demonstrate the utility of the Night Vision Integrated Performance Model (NV-IPM) image generation tool by using it to create a database of face images with controlled degradations. Available face recognition algorithms can then be used to directly evaluate camera designs using these degraded images. By controlling camera effects such as blur, noise, and sampling, we can analyze algorithm performance and establish a more complete performance standard for face acquisition cameras. The ability to accurately simulate imagery and directly test with algorithms not only improves the system design process but greatly reduces development cost.
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