A Background Modeling Scheme Based on High Efficiency Motion Classification for Surveillance Video Coding

Author(s):  
Pei Liao ◽  
Xiaofeng Huang ◽  
Huizhu Jia ◽  
Kaijin Wei ◽  
Binbin Cai ◽  
...  
2014 ◽  
Vol 23 (2) ◽  
pp. 769-784 ◽  
Author(s):  
Xianguo Zhang ◽  
Tiejun Huang ◽  
Yonghong Tian ◽  
Wen Gao

Author(s):  
Le Dao Thi Hue ◽  
Luong Pham Van ◽  
Duong Dinh Trieu ◽  
Xiem HoangVan

Video surveillance has been playing an important role in public safety and privacy protection in recent years thanks to its capability of providing the activity monitoring and content analyzing. However, the data associated with long hours surveillance video is huge, making it less attractive to practical applications. In this paper, we propose a low complexity, yet efficient scalable video coding solution for video surveillance system. The proposed surveillance video compression scheme is able to provide the quality scalability feature by following a layered coding structure that consists of one or several enhancement layers on the top of a base layer. In addition, to maintain the backward compatibility with the current video coding standards, the state-of-the-art video coding standard, i.e., High Efficiency Video Coding (HEVC), is employed in the proposed coding solution to compress the base layer. To satisfy the low complexity requirement of the encoder for the video surveillance systems, the distributed coding concept is employed at the enhancement layers. Experiments conducted for a rich set of surveillance video data shown that the proposed surveillance - distributed scalable video coding (S-DSVC) solution significantly outperforms relevant video coding benchmarks, notably the SHVC standard and the HEVC-simulcasting while requiring much lower computational complexity at the encoder which is essential for practical video surveillance applications.


2018 ◽  
Vol 20 (11) ◽  
pp. 2921-2934 ◽  
Author(s):  
Gang Wang ◽  
Bo Li ◽  
Yongfei Zhang ◽  
Jinhui Yang

Author(s):  
Gang Wang ◽  
Mingliang Zhou ◽  
Haiheng Cao ◽  
Bin Fang ◽  
Shiting Wen ◽  
...  

Perceptual video coding (PVC) optimization has been an important video coding technique, which can be consistent with the perception characteristics of the human visual system (HVS). Currently, PVC schemes incorporating the just noticeable distortion (JND) model can obtain better performance gain in all PVC schemes. To further accelerate the JND computation for real-time video coding applications (e.g. surveillance video coding and conference video coding), this paper proposes a fast perceptual surveillance video coding (PSVC) scheme based on background model-driven JND estimation method. First, to utilize the surveillance scene characteristics, the computation complexity of JND estimation can be significantly decreased by reusing the content complexity of background regions. Then we apply the perceptive video coding scheme into the background modeling-based surveillance video codec. The proposed scheme adopts background modeling frame as background anchor. Experimental results show that the proposed scheme can yield remarkable time saving of 42.33% maximum and on average 34.76% with approximate bitrate reductions and similar subjective quality, compared to HEVC and other state-of-the-art schemes.


2016 ◽  
Vol 11 (9) ◽  
pp. 764
Author(s):  
Lella Aicha Ayadi ◽  
Nihel Neji ◽  
Hassen Loukil ◽  
Mouhamed Ali Ben Ayed ◽  
Nouri Masmoudi

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