This paper proposes a novel two-step approach for face detection in complex scenes. As image capturing is strictly related to reflection of lighting, it has been observed that a face in the foreground is more vulnerable to lightness than environment in the background. The framework of the proposed method resolves mainly around the gap based on energy variation between the face and the scene. To speed up the process, this approach adopts energy analysis to face localization strategy. We present energy image analysis to remove most noise-like regions so as to enhance face localization performance, and then devise the head corner detection (HCD) approach to search for the best combinations of facial sides and head corners with anthropometric measures, and thereafter the facial interest region is located. The experimental results demonstrate that the performance of our proposed method has significant improvement on three head-and-shoulder databases, when compared with related work.