scholarly journals Optical Flow-Based Fast Motion Parameters Estimation for Affine Motion Compensation

2020 ◽  
Vol 10 (2) ◽  
pp. 729 ◽  
Author(s):  
Antoine Chauvet ◽  
Yoshihiro Sugaya ◽  
Tomo Miyazaki ◽  
Shinichiro Omachi

This study proposes a lightweight solution to estimate affine parameters in affine motion compensation. Most of the current approaches start with an initial approximation based on the standard motion estimation, which only estimates the translation parameters. From there, iterative methods are used to find the best parameters, but they require a significant amount of time. The proposed method aims to speed up the process in two ways, first, skip evaluating affine prediction when it is likely to bring no encoding efficiency benefit, and second, by estimating better initial values for the iteration process. We use the optical flow between the reference picture and the current picture to estimate quickly the best encoding mode and get a better initial estimation. We achieve a reduction in encoding time over the reference of half when compared to the state of the art, with a loss in efficiency below 1%.

2019 ◽  
Vol 28 (3) ◽  
pp. 1456-1469 ◽  
Author(s):  
Kai Zhang ◽  
Yi-Wen Chen ◽  
Li Zhang ◽  
Wei-Jung Chien ◽  
Marta Karczewicz

Sensors ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 1818 ◽  
Author(s):  
Yuan Liu ◽  
Xiubao Sui ◽  
Xiaodong Kuang ◽  
Chengwei Liu ◽  
Guohua Gu ◽  
...  

Due to the fast speed and high efficiency, discriminant correlation filter (DCF) has drawn great attention in online object tracking recently. However, with the improvement of performance, the costs are the increase in parameters and the decline of speed. In this paper, we propose a novel visual tracking algorithm, namely VDCFNet, and combine DCF with a vector convolutional network (VCNN). We replace one traditional convolutional filter with two novel vector convolutional filters in the convolutional stage of our network. This enables our model with few memories (only 59 KB) trained offline to learn the generic image features. In the online tracking stage, we propose a coarse-to-fine search strategy to solve drift problems under fast motion. Besides, we update model selectively to speed up and increase robustness. The experiments on OTB benchmarks demonstrate that our proposed VDCFNet can achieve a competitive performance while running over real-time speed.


Author(s):  
Kai Zhang ◽  
Li Zhang ◽  
Hongbin Liu ◽  
Jizheng Xu ◽  
Yue Wang

2017 ◽  
Vol 7 (5) ◽  
pp. 500 ◽  
Author(s):  
Yi-Xiong Zhang ◽  
Ru-Jia Hong ◽  
Cheng-Fu Yang ◽  
Yun-Jian Zhang ◽  
Zhen-Miao Deng ◽  
...  

Author(s):  
Tianliang Fu ◽  
Kai Zhang ◽  
Li Zhang ◽  
Shanshe Wang ◽  
Siwei Ma

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