Adaptive feature-specific imaging: a face recognition example
Adaptive feature-specific imaging: a face recognition example
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DOI：
10.1364/ao.47.000b21
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发表时间：
2008-04-01
期刊：
影响因子：
1.9
通讯作者：
Neifeld, Mark A.
中科院分区：
文献类型：
--
作者：
Baheti, Pawan K.;Neifeld, Mark A.
我们提出了一个自适应特征特定成像（AFSI）系统，并考虑其应用程序的人脸识别任务。所提出的系统利用以前的测量，以适应在每一步的投影基础。使用序贯假设检验，我们比较AFSI与静态FSI（SFSI）和静态或自适应常规成像的测量次数，以达到指定的误分类概率（P-E）。AFSI系统表现出显着的改善相比，SFSI和传统的成像在低信噪比（SNR）。结果表明，对于M = 4的假设和期望的P-e = 10（-2），AFSI需要100倍的测量比自适应常规成像器在SNR = -20 dB。我们还显示了一个权衡，在平均检测时间，测量SNR和适应优势之间，导致在每次测量的最佳值的集成时间（相当于SNR）。(C)2008年美国光学学会。
We present an adaptive feature-specific imaging (AFSI) system and consider its application to a face recognition task. The proposed system makes use of previous measurements to adapt the projection basis at each step. Using sequential hypothesis testing, we compare AFSI with static-FSI (SFSI) and static or adaptive conventional imaging in terms of the number of measurements required to achieve a specified probability of misclassification (P-e). The AFSI system exhibits significant improvement compared to SFSI and conventional imaging at low signal-to-noise ratio (SNR). It is shown that for M = 4 hypotheses and desired P-e = 10(-2), AFSI requires 100 times fewer measurements than the adaptive conventional imager at SNR = -20 dB. We also show a trade-off, in terms of average detection time, between measurement SNR and adaptation advantage, resulting in an optimal value of integration time (equivalent to SNR) per measurement. (C) 2008 Optical Society of America.