Digital Video Sequence Stabilization Based on 2.5D Motion Estimation and Inertial Motion Filtering

2001 ◽  
Vol 7 (4) ◽  
pp. 357-365 ◽  
Author(s):  
Jesse S. Jin ◽  
Zhigang Zhu ◽  
Guangyou Xu
2012 ◽  
Vol 457-458 ◽  
pp. 867-871
Author(s):  
Xi Nan Zhang ◽  
Ai Lin Liu

To reduce the complexity of AVS sub-pixel motion vector search, this paper proposes a new improved algorithm based on little diamond window searching policies according to the law of the general video sequence motion vector focusing on the near of the initial searching point at the time of the subpixel motion estimation on the basis of deeping analysis to HFPS algorithm. Comparing with the sub-pixel HFPS algorithm search algorithm, the time of sub-pixel motion estimation can reduce 51.97% on average and efficiently decrease the computational number of sub-pixel motion estimation on average PSNR lost less than 0.01dB to the video sequences with different motion characteristics.


2012 ◽  
Vol 457-458 ◽  
pp. 819-824
Author(s):  
Xi Nan Zhang ◽  
Yan Jun Gong

To reduce the complexity of AVS pixel motion vector search, this paper proposes a improved AVS pixel motion estimation UMHexagonS algorithm. The algorithm adds the improve of advanced new array and adaptive adjustment search template. To the video sequence of different motion feature, compare with UMHexagonS algorithm, in the case of mean PSNR descend less than 0.01dB and bitrate only mean increase 0.54%, the time of pixel motion estimation is reduced by 8.72%~20.25% and the calculated amount of pixel motion estimation is also reduced.


2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Guo Qing ◽  
HuBao Hui

Aiming at the difficulty of standardizing the action of basketball shooting training, a new method of standardizing the action of basketball shooting training is proposed based on digital video technology. The digital video signal representation, video sequence coding data structure, and video sequence compression coding method are analyzed, and the pixels of basketball shooting training action position space are sampled to collect basketball shooting training images. The time difference method is used to extract the movement target of basketball shooting training from a digital video sequence. Based on digital video technology, the initial background image is estimated, and the update rate is introduced to update the background estimation image. According to the pixel value sequence of the basketball shooting training image, the pixel model of the basketball shooting training image is defined and modified. By judging whether the defined pixel value matches the background parameter model, the standardization of shooting training can be realized. The experimental results show that the proposed method has good stability, high precision, and short time in determining the standardization of shooting movement, can correct the wrong shooting movement in real time, and can effectively guide basketball shooting training.


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