Detecting Faces in Images: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer Vision
A Color-Triangle-Based Approach to the Detection of Human Face
BMVC '00 Proceedings of the First IEEE International Workshop on Biologically Motivated Computer Vision
Providing the basis for human-robot-interaction: a multi-modal attention system for a mobile robot
Proceedings of the 5th international conference on Multimodal interfaces
Video-Based Framework for Face Recognition in Video
CRV '05 Proceedings of the 2nd Canadian conference on Computer and Robot Vision
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Face detection using quantized skin color regions merging andwavelet packet analysis
IEEE Transactions on Multimedia
A highly efficient system for automatic face region detection in MPEG video
IEEE Transactions on Circuits and Systems for Video Technology
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Face detection has been a key step in face analysis systems for decades. However, it is still a challenging task due to the variation in image background, view, pose, facial expression, etc. This paper proposes a simple and effective tool to detect human faces in moving pictures under such conditions. An improved approach aiming to reduce impacts of illumination, scale and connection of faces to receive rapidly skin homogeneous regions considered as the most potential face candidates is presented. A cascade-typed hybrid classifier, applied in retrieved face candidates, is based on template matching and appearance-based method providing a robust detection of multiply posed and viewed faces. This verification achieves advantages of the powerful discrimination of Local Binary Patterns (LBPs) and the high speed detection capability of embedded Hidden Markov Models (eHMMs). Experiments were performed out with different image databases and video sequences so that the system shows effective to detect human face for real-time uses.