Vector Quantization-Based Motion Field Segmentation under the Entropy Criterion

Dufaux, Frédéric; Moccagatta, I.; Moscheni, F.; Nicolas, Henri

doi:10.1006/jvci.1994.1034

Cited by 15 publications

(14 citation statements)

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“…In [72], blocks corresponding to moving edges are segmented, taking into account the infor mation of the previous fr ame. Similarly, another approach which segments the block-based motion fi eld by means of vector quantization (VQ) has been proposed [73], [74] . In this method, blocks which contain several objects moving in different directions are segmented.…”

Section: Locally Adaptive Multigrid Block Matching Motion Estimationmentioning

confidence: 99%

Motion estimation techniques for digital TV: a review and a new contribution

1995

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The key to high performance in image sequence coding lies in an efficient reduction of the temporal redundancies. For this purpose, motion estimation and compensation techniques have been suc cessfully applied. This paper studies motion estimation algorithms in the context of fi rst generation coding techniques commonly used in digital TV. In this framework, estimating the motion in the scene is not an intrinsic goal. Motion estimation should indeed provide good temporal prediction and simultaneously require low overhead information. More specifically, the aim is to minimize globally the bandwidth corresponding to both the prediction error information and the motion parameters. This paper first clarifies the notion of motion, reviews classical motion estimation tech niques, and outlines new perspectives. Block matching techniques are shown to be the most appropriate in the framework of first generation coding. To overcome the drawbacks characteristic of most block matching techniques, this paper proposes a new locally adaptive multigrid block matching motion estimation technique.This algorithm has been designed taking into account the above aims. It leads to a robust motion field estimation, precise prediction along moving edges and a decreased amount of side information in uniform areas. Furthermore, the algorithm controls the accuracy of the motion estimation procedure in order to optimally balance the amount of information corresponding to the prediction error and to the motion parameters. Experimental results show that the technique results in greatly enhanced visual quality and significant saving in terms of bit rate when compared to classical block matching techniques.

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Section: Locally Adaptive Multigrid Block Matching Motion Estimationmentioning

confidence: 99%

Motion estimation techniques for digital TV: a review and a new contribution

1995

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“…Several studies have shown the relevance of parametric models for motion estimation and segmentation [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17]. Most regarded estimation and segmentation as successive processes when these are mutually dependent.…”

Section: Introductionmentioning

confidence: 99%

Joint multiregion segmentation and parametric estimation of image motion by basis function representation and level set evolution

Vázquez

Mitiche

Laganière

2006

IEEE Trans. Pattern Anal. Machine Intell.

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Abstract-The purpose of this study is to investigate a variational method for joint segmentation and parametric estimation of image motion by basis function representation of motion and level set evolution. The functional contains three terms. One term is of classic regularization to bias the solution toward a segmentation with smooth boundaries. A second term biases the solution toward a segmentation with boundaries which coincide with motion discontinuities, following a description of motion discontinuities by a function of the image spatio-temporal variations. The third term refers to region information and measures conformity of the parametric representation of the motion of each region of segmentation to the image spatio-temporal variations. The components of motion in each region of segmentation are represented as functions in a space generated by a set of basis functions. The coefficients of the motion components considered combinations of the basis functions are the parameters of representation. The necessary conditions for a minimum of the functional, which are derived taking into consideration the dependence of the motion parameters on segmentation, lead to an algorithm which condenses to concurrent curve evolution, implemented via level sets, and estimation of the parameters by least squares within each region of segmentation. The algorithm and its implementation are verified on synthetic and real images using a basis of cosine transforms.

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“…When the blocks contain objects with different motions, the segmentation is performed along the moving boundaries of such objects. In previous versions of the algorithm, artificial codebooks have been used [11,12], and in [12] it has been shown that a 2 regions segmentation is a good compromise between performance and complexity. In this paper, the codebook is derived by means of the LBG [13] algorithm trained on patterns obtained by segmenting natural images [14].…”

Section: Introductionmentioning

confidence: 99%

“…The approach is based on segmentation and Vector Quantization (VQ) [11]. The segmentation patterns are chosen among a set of pre-defined patterns, constituting the codebook, by means of a minimization criterion.…”

Section: Introductionmentioning

confidence: 99%

<title>Vector quantization (VQ)-based motion field refinement technique for image sequence coding</title>

Moccagatta

Schuetz

Moscheni

et al. 1995

Advanced Image and Video Communications and Storage Technologies

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To reduce temporal redundancies appearing in video sequences, block based motion estimation techniques have been successfully applied. However, due to the block-based model, blocking artifacts appear in the resulting displaced frame difference, reducing the global coding scheme efficiency.In this paper, a motion field refinement technique is proposed to overcome these artifacts. The method is based on segmentation and Vector Quantization (VQ). The motion field resulting from the block-based motion estimation is segmented using a set of patterns stored in a codebook. These patterns are derived by the LBG algorithm trained on natural edges. The VQ technique allows a low cost data transmission of the segmentation information. Finally, the segmentation is controlled by an entropy criterion, which performs an optimal bit allocation between motion, segmentation and DFD information. Simulation results show that a significant improvement is achieved using the proposed method. In particular moving edges are much better motion compensated and the visual quality is greatly enhanced.

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Vector Quantization-Based Motion Field Segmentation under the Entropy Criterion

Cited by 15 publications

References 0 publications

Motion estimation techniques for digital TV: a review and a new contribution

Motion estimation techniques for digital TV: a review and a new contribution

Joint multiregion segmentation and parametric estimation of image motion by basis function representation and level set evolution

<title>Vector quantization (VQ)-based motion field refinement technique for image sequence coding</title>

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