Fire detection using statistical color model in video sequences
Journal of Visual Communication and Image Representation
Camera Motion Analysis in On-line MPEG Sequences
WIAMIS '07 Proceedings of the Eight International Workshop on Image Analysis for Multimedia Interactive Services
A Moving Object Segmentation in MPEG Compressed Domain Based on Motion Vectors and DCT Coefficients
CISP '08 Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 3 - Volume 03
Overview of the H.264/AVC video coding standard
IEEE Transactions on Circuits and Systems for Video Technology
A moving object detection scheme in codestream domain for motion JPEG encoded movies
PCM'10 Proceedings of the Advances in multimedia information processing, and 11th Pacific Rim conference on Multimedia: Part II
Semantic web technologies for video surveillance metadata
Multimedia Tools and Applications
ANN face detection with skin color distribution rules
Machine Graphics & Vision International Journal
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Journal of Visual Communication and Image Representation
Lane mark segmentation and identification using statistical criteria on compressed video
Integrated Computer-Aided Engineering
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In this paper a novel method is presented to detect moving objects in H.264/AVC [T. Wiegand, G. Sullivan, G. Bjontegaard, G. Luthra, Overview of the H.264/AVC video coding standard, IEEE Transactions on Circuits and Systems for Video Technology, 13 (7) (2003) 560-576] compressed video surveillance sequences. Related work, within the H.264/AVC compressed domain, analyses the motion vector field to find moving objects. However, motion vectors are created from a coding perspective and additional complexity is needed to clean the noisy field. Hence, an alternative approach is presented here, based on the size (in bits) of the blocks and transform coefficients used within the video stream. The system is restricted to the syntax level and achieves high execution speeds, up to 20 times faster than the related work. To show the good detection results, a detailed comparison with related work is presented for different challenging video sequences. Finally, the influence of different encoder settings is investigated to show the robustness of our system.