Neural Network-Based Face Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Example-Based Learning for View-Based Human Face Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Example-Based Object Detection in Images by Components
IEEE Transactions on Pattern Analysis and Machine Intelligence
WACV '96 Proceedings of the 3rd IEEE Workshop on Applications of Computer Vision (WACV '96)
Support vector machines: training and applications
Support vector machines: training and applications
Learning and example selection for object and pattern detection
Learning and example selection for object and pattern detection
A statistical approach to 3d object detection applied to faces and cars
A statistical approach to 3d object detection applied to faces and cars
Face detection with the modified census transform
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Facial expression transformations for expression-invariant face recognition
ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part I
Pose robust human detection using multiple oriented 2d elliptical filters
VNBA '08 Proceedings of the 1st ACM workshop on Vision networks for behavior analysis
Facial fraud discrimination using detection and classification
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part III
ICIRA'12 Proceedings of the 5th international conference on Intelligent Robotics and Applications - Volume Part II
Vision-based arm gesture recognition for a long-range human---robot interaction
The Journal of Supercomputing
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In this paper, we present a robust real-time face detection algorithm. We improved the conventional face detection algorithms for three different steps. For preprocessing step, we revise the modified census transform to compensate the sensitivity to the change of pixel values. For face detection step, we propose difference of pyramid(DoP) images for fast face detection. Finally, for postprocessing step, we propose face certainty map(FCM) which contains facial information such as facial size, location, rotation, and confidence value to reduce FAR(False Acceptance Rate) with constant detection performance. The experimental results show that the reduction of FAR is ten times better than existing cascade adaboost detector while keeping detection rate and detection time almost the same.