Neither novel nor useful
As the chief scientist of a company developing face recongition technology for the banking industry, I have to say I feel that these published results are very misleading. This paper demonstrates little or no understanding of what is actually entailed in evaluation of real world biometric systems. Tests with this few participants are not statistically valid and should not be used to infer the performance of a system on a larger database. I am actually shocked that they made it into a well known peer reviewed journal such as Science with this result.
Leaving aside the question of whether 100% recognition is achievable in reality, the truth is that achieving *near* 100% recognition on a set of 25 people is not impressive and can be done with any of a variety of techniques. The recent FRVT results demonstrate that several software platforms can achieve near 100% performance over much larger databases than this paper discusses.
IMO, the challenge in face recognition today is not differentiating faces among a small group of people, it is dealing with very large databases of people (millions) using images collected in a completely uncontrolled environment. I don't see this technique being useful particularly in this endeavor. Also, as one poster has already mentioned, the technique is related to the active appearance work of Cootes but less powerful. The technique of simply averaging patterns to reduce noise is well known and has been used previously in many applications.
In sum, I don't believe that this work is either novel or particularly useful and I don't beleive the result will apply to more challenging applications such as surveillance.
Biting the hand that feeds IT
