SNoW: Understanding the causes of strong, neutral, and weak face impostor pairs

The Strong, Neutral, or Weak Face Impostor Pairs problem was generated to explore the causes and impact of impostor face pairs that span varying strengths of scores. We develop three partitions within the impostor distribution for a given algorithm. The Strong partition contains image pairs that are easy to categorize as impostors. The Neutral partition contains image pairs that are less easily categorized as impostors. The Weak partition contains image pairs that are likely to cause false positives. Three algorithms, and the fusion of their scores, were used to analyze the performance of these three partitions using the same set of authentic scores employed in the Face Recognition Vendor Test (FRVT) 2006 Challenge Dataset. The results of these experiments provide evidence that varying degrees of impostor scores impact the overall performance and thus the underlying causes of weak impostor pairs are worthy of further exploration.