Vehicle Driver Face Detection in Various Sunlight Environments Using Composed Face Images

The purpose of this study is to increase the face detection accuracy in vehicle cabin. Although existing face detectors employed in consumer applications already have sufficient face detection accuracy for many situations, we revealed that detection rate of existing face detector is drastically decreased by shadow on the driver's face caused by sunlight whose relative direction to the driver is continuously changed while driving. In order to overcome this problem, we increase the number of driver's faces in training dataset by synthesizing the shadowed driver's faces from various directions of sunlight which are created using an image composing technique. In experiment, we found that the 20% to 40% shadowed faces should be blended into training dataset in terms of the generality and the adaptability for robust drivers' face detection.

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