Affine Motion Prediction Based on Translational Motion Vectors

Kordasiewicz, R.C.; Gallant, M.; Shirani, Shahram

doi:10.1109/tcsvt.2007.903777

Cited by 55 publications

(27 citation statements)

References 14 publications

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“…It should be noted that the proposed method does not have the procedure to detect the zoom motion before the generation of zoomed frames like [9][10][11]. In such design, number of zoomed frames and the zooming factors for these frames should be pre-determined.…”

Section: 3mentioning

confidence: 99%

“…Another approach is to use a more general affine model [9][10][11] involving translation, rotation and zoom motion to increase the prediction accuracy. In [9], affine parameter sets are estimated and multiple "wrapped" frames are generated based on the parameter sets as references and the affine parameters are transmitted if the block in a wrapped frame is selected as the best prediction candidate.…”

Section: Introductionmentioning

confidence: 99%

“…In [9], affine parameter sets are estimated and multiple "wrapped" frames are generated based on the parameter sets as references and the affine parameters are transmitted if the block in a wrapped frame is selected as the best prediction candidate. In [10], motion vectors of other blocks are used to make an affine transformed block as a searching candidate. It focuses on local complex general motion.…”

Section: Introductionmentioning

confidence: 99%

“…This paper presents the promising results of our preliminary study on applying this MCP model to video coding. It should be noted that the major difference between this work and the methods in [9][10][11] is that our method does not require affine parameter estimation for generating additional reference frames. Zoomed reference frames are indicated as the index of selected zoomed frame similar to MRF, thus no side information about zoom scale is needed to be transmitted.…”

Section: Introductionmentioning

confidence: 99%

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Block-Matching Translation And Zoom Motion-Compensated Prediction by sub-sampling

Wong

Cheung

et al. 2009

2009 16th IEEE International Conference on Image Processing (ICIP)

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-In modern video coding standards, motion compensated prediction (MCP) plays a key role to achieve video compression efficiency. Most of them make use of block matching techniques and assume the motions are pure translational. Attempts toward a more general motion model are usually too complex to be practical in near future. In this paper, a new Block-Matching Translation and Zoom Motion-Compensated Prediction (BTZMP) is proposed to extend the pure translational model to a more general model with zooming. It adopts the camera zooming and object motions that becomes zooming while projected on video frames. Experimental results show that BTZMP can give prediction gain up to 2.25dB for various sequences compared to conventional block-matching MCP. BTZMP can also be incorporated with multiple reference frames technique to give extra improvement, evidentially by the prediction gain ranging from 2.03 to 3.68dB in the empirical simulations.

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Section: 3mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Block-Matching Translation And Zoom Motion-Compensated Prediction by sub-sampling

Wong

Cheung

et al. 2009

2009 16th IEEE International Conference on Image Processing (ICIP)

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“…The additional complex motion is predict by using the motion information from nearest neighbors. Roman et al [5] proposed an affine motion field prediction based on translational Motion Vectors (MVs) for better modeling complex motion, which is used as a postprocessing step after mode decision and Motion Estimation (ME). A parametric skip mode based on higher-order parametric motion model is presented in [3] for better prediction of complex motion.…”

Section: Introductionmentioning

confidence: 99%

The Face Object based HEVC System for Video Call

Wang¹,

Yan²,

Huang³

et al. 2015

Proceedings of the 8th International Conference on Mobile Multimedia Communications

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Guaranteing the quality of face object in video call is the key task for video coding systems under the constrained bandwidth of network. Conventionally, the face object is divided into disperse blocks under the hybrid coding framework. Therefore, the characteristics of the complete face object have not been fully used. Meanwhile, it is difficult to predict the complex affine transformations such as rotation and scaling of the face object in neighboring frames based on the current translation motion model.In this paper, we propose an improved video coding scheme for video call. The complex transformation of complete face object is used to improve the compression effect. Experimental results show that our proposed method has better performance compared with HM12.0, the bits rate saving of face region is up to 19.59% under the similar visual quality .

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Replacing Conventional Motion Estimation with Affine Motion Prediction for High-Quality Video Coding

Cheung

Siu

2012

The Era of Interactive Media

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Affine Motion Prediction Based on Translational Motion Vectors

Cited by 55 publications

References 14 publications

Block-Matching Translation And Zoom Motion-Compensated Prediction by sub-sampling

Block-Matching Translation And Zoom Motion-Compensated Prediction by sub-sampling

The Face Object based HEVC System for Video Call

Replacing Conventional Motion Estimation with Affine Motion Prediction for High-Quality Video Coding

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