Motion vector quantization for efficient low-bit-rate video coding

Cagnazzo, Marco; Agostini, Marie; Antonini, Marc; Laroche, Guillaume; Jung, Joël

doi:10.1117/12.805857

Cited by 4 publications

(7 citation statements)

References 4 publications

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“…The results in [8], however interesting they are, were limited by the fact that we only considered 16x16 MB in motion estimation. This was reasonable as first approach, above all when very low coding rates are considered.…”

Section: Introductionmentioning

confidence: 71%

“…We have presented in [8] some results for the QMV16x16 coding mode, which was reasonable for a first analysis. However, in order to better understand the usefulness of the 16x16 mode, it is necessary to test it when smaller partitions are enabled.…”

Section: Quantization Of Motion Vectorsmentioning

confidence: 97%

“…In this section we recall the main properties of the QMV mode described in [8]. This mode was implemented within the JM implementation of H.264/AVC.…”

Section: Quantization Of Motion Vectorsmentioning

confidence: 99%

“…On the other hand, if the coding mode is really adapted to some specific circumstances, it can have a less RD cost and be selected for some MB. In [8] we shown that in many cases the gain associated to the new mode are larger than the losses, so it is worth using this new mode, especially for sequences with an important motion. To this end, it was instrumental to use scalar quantization of motion vectors and a RD-optimized selection of the modes.…”

Section: Introductionmentioning

confidence: 96%

See 3 more Smart Citations

Improving H.264 performances by quantization of motion vectors

Corrado¹,

Agostini²,

Cagnazzo

et al. 2009

2009 Picture Coding Symposium

Self Cite

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The coding resources used for motion vectors (MVs) can attain quite high ratios even in the case of efficient video coders like H.264, and this can easily lead to suboptimal rate-distortion performance. In a previous paper, we proposed a new coding mode for H.264 based on the quantization of motion vectors (QMV). We only considered the case of 16x16 partitions for motion estimation and compensation. That method allowed us to obtain an improved trade-off in the resource allocation between vectors and coefficients, and to achieve better rate-distortion performances with respect to H.264. In this paper, we build on the proposed QMV coding mode, extending it to the case of macroblock partition into smaller blocks. This issue requires solving some problems mainly related to the motion vector coding. We show how this task can be performed efficiently in our framework, obtaining further improvements over the standard coding technique. INTRODUCTIONThe trade-off between allocation of coding resources to motion vectors (MV) or to transform coefficients has a major importance when it comes to efficient video coding techniques. Nevertheless, in video coding standards [1, 2], there is not much flexibility at this end: generally it is only possible to indirectly choose how the bit-rate is shared between motion and residual by selecting one among the several available coding modes for each macroblock (MB). Therefore, in several prior works, it has been noted that when a sequence is encoded at low and very low bit-rates, a large quota of resources is allocated to MVs [3]. This suggests that, in the framework of a H.264/AVC-like coder, there could be room for improvement if some new coding mode with less costly motion information is introduced, for example by quantizing the motion vectors.The quantization of MVs has been an active research topic since the mid'90 [4,5], but in these works the proposed approach was mainly a vector quantization (VQ) of MVs, with quantized vectors used both at the encoder and decoder sides (closed loop). For example in [6] a RD-optimized codebook for VQ of MVs is designed. In [7] a model based optimization of the MV precision is proposed, but here we are focused on a data-driven solution rather than a model-based one. In particular we are interested in the use of a new coding mode based on motion vector quantization.However it should be noticed that any new mode introduced into a H.264-like coder causes an increase of the coding rate, because it is more costly to signal the chosen coding mode among

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Section: Introductionmentioning

confidence: 71%

Section: Quantization Of Motion Vectorsmentioning

confidence: 97%

“…In this section we recall the main properties of the QMV mode described in [8]. This mode was implemented within the JM implementation of H.264/AVC.…”

Section: Quantization Of Motion Vectorsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 96%

See 2 more Smart Citations

Improving H.264 performances by quantization of motion vectors

Corrado¹,

Agostini²,

Cagnazzo

et al. 2009

2009 Picture Coding Symposium

Self Cite

View full text Add to dashboard Cite

show abstract

“…In [8], a new Inter coding mode, using quantized motion vectors, is introduced. Competing with other modes, it takes care of better distributing bits ressources between texture and residual motion vectors.…”

Section: B Recent Motion Vector Coding Improvementsmentioning

confidence: 99%

Motion vector forecast and mapping (MV-FMap) method for entropy coding based video coders

Tanou

Thiesse

Jung

et al. 2010

2010 IEEE International Workshop on Multimedia Signal Processing

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Abstract-Since the finalization of the H.264/AVC standard and in order to meet the target set by both ITU-T and MPEG to define a new standard that reaches 50% bit rate reduction compared to H.264/AVC, many tools have efficiently improved the texture coding and the motion compensation accuracy. These improvements have resulted in increasing the proportion of bit rate allocated to motion information. Thus, the bit rate reduction of this information becomes a key subject of research. This paper proposes a method for motion vector coding based on an adaptive redistribution of motion vector residuals before entropy coding. Motion information is gathered to forecast a list of motion vector residuals which are redistributed to unexpected residuals of lower coding cost. Compared to H.264/AVC, this scheme provides systematic gain on tested sequences, and 2.3% in average, reaching up to 4.9% for a given sequence.

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