Journal ArticleDOI
Efficient and Low-Complexity Surveillance Video Compression Using Backward-Channel Aware Wyner-Ziv Video Coding
Limin Liu,Zhen Li,Edward J. Delp +2 more
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TLDR
A surveillance video compression system with low-complexity encoder based on Wyner-Ziv coding principles and an error resilience scheme for BCAWZ to address the concern of reliable transmission in the backward-channel, which is essential to the quality of video data for real-time and reliable object detection and event analysis.Abstract:
Video surveillance has been widely used in recent years to enhance public safety and privacy protection. A video surveillance system that deals with content analysis and activity monitoring needs efficient transmission and storage of the surveillance video data. Video compression techniques can be used to achieve this goal by reducing the size of the video with no or small quality loss. State-of-the-art video compression methods such as H.264/AVC often lead to high computational complexity at the encoder, which is generally implemented in a video camera in a surveillance system. This can significantly increase the cost of a surveillance system, especially when a mass deployment of end cameras is needed. In this paper, we discuss the specific considerations for surveillance video compression. We present a surveillance video compression system with low-complexity encoder based on Wyner-Ziv coding principles to address the tradeoff between computational complexity and coding efficiency. In addition, we propose a backward-channel aware Wyner-Ziv (BCAWZ) video coding approach to improve the coding efficiency while maintaining low complexity at the encoder. The experimental results show that for surveillance video contents, BCAWZ can achieve significantly higher coding efficiency than H.264/AVC intra coding as well as existing Wyner-Ziv video coding methods and is close to H.264/AVC inter coding, while maintaining similar coding complexity with intra coding. This shows that the low motion characteristics of many surveillance video contents and the low-complexity encoding requirement make our scheme a particularly suitable candidate for surveillance video compression. We further propose an error resilience scheme for BCAWZ to address the concern of reliable transmission in the backward-channel, which is essential to the quality of video data for real-time and reliable object detection and event analysis.read more
Citations
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Journal ArticleDOI
Motion segmentation-based surveillance video compression using adaptive particle swarm optimization
TL;DR: A hybrid video compression approach with the help of foreground motion compensation for smart surveillance, which works effectively by including the advantages of both block-based and object-based coding techniques as well as reducing the drawbacks of both.
Journal ArticleDOI
Low-Complexity Video Coding Based on Two-Dimensional Singular Value Decomposition
TL;DR: A low-complexity video coding scheme based upon 2-D singular value decomposition (2-D SVD), which exploits basic temporal correlation in visual signals without resorting to motion estimation (ME), which is for the better compromise of computational complexity and temporal redundancy reduction.
Journal ArticleDOI
Skip Decision and Reference Frame Selection for Low-Complexity H.264/AVC Surveillance Video Coding
Pushkar Gorur,Bharadwaj Amrutur +1 more
TL;DR: Two techniques to reduce the bandwidth and computational cost of static camera surveillance video encoders without affecting detection and recognition performance are proposed.
Journal ArticleDOI
Encoder adaptable difference detection for low power video compression in surveillance system
Xin Jin,Satoshi Goto +1 more
TL;DR: A difference detection algorithm is proposed to reduce the computational complexity and power consumption in surveillance video compression by automatically distributing the video data to different modules of the video encoder according to their content similarity features.
Book ChapterDOI
Encoder adaptable difference detection for low power video compression in surveillance system
Xin Jin,Satoshi Goto +1 more
TL;DR: A difference detection algorithm is proposed to reduce the computational complexity and power consumption in surveillance video compression and provides high adaptability to be integrated into the existing H.264/AVC video encoders.
References
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