A new motion detection algorithm based on Σ-Δ background estimation
Pattern Recognition Letters
Complexity control strategy for real-time H.264/AVC encoder
IEEE Transactions on Consumer Electronics
Statistical Background Subtraction Using Spatial Cues
IEEE Transactions on Circuits and Systems for Video Technology
An Advanced Motion Detection Algorithm With Video Quality Analysis for Video Surveillance Systems
IEEE Transactions on Circuits and Systems for Video Technology
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Motion detection plays an important role in the video surveillance system. Video communications over wireless networks can easily suffer from network congestion or unstable bandwidth, especially for embedded application. A rate control scheme produces various bit-rate video streams to match the available network bandwidth. However, effective detection of moving objects in various bit-rate video streams is a very difficult problem. This paper proposes an advanced approach based on the counter-propagation network through artificial neural networks to achieve effective moving object detection in various bit-rate video streams. We compare our method with other state-of-the-art methods. To demonstrate the performance of our proposed method in regard to object extraction, we analyze qualitative and quantitative comparisons in real-world limited bandwidth networks over a wide range of natural video sequences. The overall results show that our proposed method substantially outperforms other state-of-the-art methods by Similarity and F1 accuracy rates of 73.84% and 84.94%, respectively.