Name
Title | ||
|---|---|---|
Counter-propagation artificial neural network-based motion detection algorithm for static-camera surveillance scenarios. |
Abstract | ||
|---|---|---|
Motion detection plays an important role in most static-camera video surveillance systems, yet video communications over wireless networks can easily suffer from network congestion or unstable bandwidth, especially for embedded applications. A rate control scheme produces variable bit rate video streams to match the available network bandwidth. However, effectively detecting moving objects in a variable bit rate video stream is a considerable challenge. This paper proposes an advanced approach based on a counter-propagation artificial neural network to achieve effective moving-object detection in such conditions. Qualitative and quantitative tests over real-world limited bandwidth networks show that the proposed method substantially outperforms other state-of-the-art methods. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.neucom.2017.08.002 | Neurocomputing |
Keywords | Field | DocType |
Motion detection,Video surveillance,Neural network | Wireless network,Motion detection,Computer science,Real-time computing,Video tracking,Bandwidth (signal processing),Network congestion,Artificial neural network,Network traffic control,Variable bitrate | Journal |
Volume | ISSN | Citations |
273 | 0925-2312 | 0 |
PageRank | References | Authors |
0.34 | 22 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bo-Hao Chen | 1 | 244 | 21.00 |
| Shih-Chia Huang | 2 | 657 | 42.31 |
| Jui-Yu Yen | 3 | 2 | 0.70 |