ICIAR '09 Proceedings of the 6th International Conference on Image Analysis and Recognition
An adaptive vision system toward implicit human computer interaction
UAHCI'07 Proceedings of the 4th international conference on Universal access in human-computer interaction: ambient interaction
A theoretical approach to construct highly discriminative features with application in AdaBoost
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part I
Vision and RFID data fusion for tracking people in crowds by a mobile robot
Computer Vision and Image Understanding
Pose estimation from multiple cameras based on Sylvester's equation
Computer Vision and Image Understanding
A real-time framework for eye detection and tracking
Journal of Real-Time Image Processing
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Technologies for real-time multi-view face detection from video streams are indispensable to video content- based retrieval systems and video surveillance systems.. In this paper, we proposed a solution for real-time multi-view face detection and pose estimation in video stream. Integrating both asymmetric and symmetric rectangle features, AdaBoost learning algorithm and pyramid like architecture is employed. Asymmetric Rectangle Features (ARFs) are inherited from Symmetric Rectangle Features (SRF) to reasonably interpret asymmetric gray distribution in profile face image. Pose estimation for multi-view faces are brought out by View-Based Weighting Algorithm (VBWA). Our primary experiments demonstrated that the system achieved high accuracy and high speed to detect both front and profile faces with their pose information from soccer video streams.