Object-based coding of stereo image sequences using joint 3-D motion/disparity compensation

Tzovaras, Dimitrios; Grammalidis, N.; Strintzis, Michael G.

doi:10.1109/76.564110

Cited by 99 publications

(70 citation statements)

References 16 publications

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“…Interframe depth map or disparity ÿeld encoding may then be based on the motion information available in the MPEG or S-MPEG bitstream. Likewise, in region-based or object-based stereo [6,14,28,29,35] and multiview encoders=decoders, the available 3D object-based motion information may also be used for the e cient coding of depth maps or disparity ÿelds.…”

Section: Introductionmentioning

confidence: 99%

Disparity field and depth map coding for multiview 3D image generation

Tzovaras

Grammalidis

Strintzis

1998

Signal Processing: Image Communication

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Section: Introductionmentioning

confidence: 99%

Disparity field and depth map coding for multiview 3D image generation

Tzovaras

Grammalidis

Strintzis

1998

Signal Processing: Image Communication

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“…Lossy or lossless techniques for the transmission of such dense disparity elds were investigated in 6,7]. Lossless transmission was estimated to require bitrates as high as 1Mbps for 720 576 pixel sized image sequences 6].…”

Section: Introductionmentioning

confidence: 99%

Motion and disparity field estimation using rate-distortion optimization

Tzovaras

Strintzis

1998

IEEE Trans. Circuits Syst. Video Technol.

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A rate-distortion framework is used to de ne a displacement v ector-eld estimation technique for use in video coding. This technique achieves maximum reconstructed image quality under the constraint of a target bitrate for the coding of the vector sequence. The technique may be adapted so as to limit its smoothing e ect to homogeneous areas and avoid highly textured areas and edges. Use of this technique is evaluated for two application areas in which the need for high compression of displacement v ector elds is particularly acute. The rst is motion-eld coding for very low bit rate image sequence transmission as in videophone applications. The second application area is coding for the transmission of dense disparity elds. This is needed for the generation at the receiver of intermediate viewpoints through spatial interpolation. It is also needed in a number of other applications requiring accurate depth knowledge, including 3D medical data transmission and transmission of scenes to be postprocessed using depth-keyed segmentation. Experimental results illustrating the performance of the proposed technique in these application areas are presented and evaluated.Subject terms: Very low bit-rate coding rate-distortion theory vector eld coding depth map coding. This work was supported by the EU CEC Project PANORAMA (ACTS project 092) and the COST 211ter project.

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“…While several approaches have been proposed to address these issues, most recent approaches rely on the analysis of the content of the medium in semantic objects. This is true both for still image manipulation (image indexing [2], [4], [7], [19], region-of-interest coding using the JPEG2000 standard [35]) and for video representation [23], coding [14], [44] and indexing using the MPEG-4 [38] and recently in- troduced MPEG-7 [29] standards. In still image indexing, for example, state of the art systems are based on the segmentation of images into regions corresponding to objects and the use of a separate set of indexing features for each object [2], [7].…”

Section: Introductionmentioning

confidence: 99%

Still Image Segmentation Tools for Object-Based Multimedia Applications

Mezaris

Kompatsiaris

Strintzis

2004

Int. J. Patt. Recogn. Artif. Intell.

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Abstract-In this paper, a color image segmentation algorithm and an approach to large-format image segmentation are presented, both focused on breaking down images to semantic objects for object-based multimedia applications. The proposed color image segmentation algorithm performs the segmentation in the combined intensitytexture-position feature space in order to produce connected regions that correspond to the real-life objects shown in the image. A preprocessing stage of conditional image filtering and a modified K-Means-with-connectivity-constraint pixel classification algorithm are used to allow for seamless integration of the different pixel features. Unsupervised operation of the segmentation algorithm is enabled by means of an initial clustering procedure. The large-format image segmentation scheme employs the aforementioned segmentation algorithm, providing an elegant framework for the fast segmentation of relatively large images. In this framework, the segmentation algorithm is applied to reduced versions of the original images, in order to speed-up the completion of the segmentation, resulting in a coarse-grained segmentation mask. The final fine-grained segmentation mask is produced with partial reclassification of the pixels of the original image to the already formed regions, using a Bayes classifier. As shown by experimental evaluation, this novel scheme provides fast segmentation with high perceptual segmentation quality.

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Object-based coding of stereo image sequences using joint 3-D motion/disparity compensation

Cited by 99 publications

References 16 publications

Disparity field and depth map coding for multiview 3D image generation

Disparity field and depth map coding for multiview 3D image generation

Motion and disparity field estimation using rate-distortion optimization

Still Image Segmentation Tools for Object-Based Multimedia Applications

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