利用多重亮度紅外線打光器之夜間人臉辨識

Abstract

在目前一般夜間監控的環境下，常常因光源的不足，無法取得較遠之清晰人物；另一方面，在光源充足的情況下，也可能因人物離攝影機過近，造成人物過曝的情形，以致於無法辨識其面貌五官。對此，我們使用週期性改變光源強度之多重亮度紅外線打光器，來輔助夜視攝影，以得到多種亮度影像，並對此新式夜視影像做分析，以期同時達到遠處人物偵測正確與近處人物清晰辨識之目的。由於透過多重亮度打光器會產生不同亮度的人臉，我們提出亮度偵測方法以分辨出高品質的人臉影像，實驗結果顯示，在不同的距離下，我們可以偵測並挑選出好的人臉影像。

In nighttime video surveillance, the image details of far objects are often hard to be identified due to poor illumination conditions while the image regions of near objects may be whitened due to overexposure. To alleviate the two problems simultaneously for nighttime video surveillance, we adopt a new multi-intensity infrared illuminator as a supportive light source to provide multiple illumination levels periodically. By using the illuminator with multiple degrees of illumination power, both far and near objects can be clearly captured. In this thesis, an effective algorithm is developed to pick out high quality human faces from nighttime video sequences. Experiment results show that well exposed face images can be automatically detected and selected for people located at various distances from the camera.