Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning Patterns of Activity Using Real-Time Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
W4: Real-Time Surveillance of People and Their Activities
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition: Features Versus Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
Elliptical Head Tracking Using Intensity Gradients and Color Histograms
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
AVSS '03 Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
Digital Image Processing (3rd Edition)
Digital Image Processing (3rd Edition)
A neuro-fuzzy approach for segmentation of human objects in image sequences
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Real-time video-shot detection for scene surveillance applications
IEEE Transactions on Image Processing
Fast and automatic video object segmentation and tracking for content-based applications
IEEE Transactions on Circuits and Systems for Video Technology
Facial fraud discrimination using detection and classification
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part III
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Real time automatic alarm systems play an essential role in security management, as evidenced by the surveillance cameras installed in nearly all automated teller machines (ATMs). Whereas manual video surveillance requires constant staff monitoring, fatigue or distraction is a common human error. Therefore, this work presents an effective detection system for facial occlusion to assist security personnel in surveillance by providing both valuable information for further video indexing applications and important clues for investigating a crime. A series of methods that include identifying and segmenting moving objects is formed. The moving edge is then captured using change detection of the inter-frame difference and the Sobel operator. Next, a Straight Line Fitting (MSLF) algorithm is developed to merge the splitting blobs. Additionally, a mechanism involving moving forward or backward justification is used to determine whether an individual is approaching a camera. Moreover, the lower boundary of a head is computed, followed by use of an elliptical head tracker to match the head region. Finally, skin area ratio is calculated to determine whether the face is occluded or not. The proposed detection system can achieve 100% and 96.15% accuracy for non-occlusive and occlusive detection, respectively, at a speed of up to 20 frames per second.