Region-of-Interest 3D Video Coding Based on Depth Images

Karlsson, Linda; Sjöström, Mårten

doi:10.1109/3dtv.2008.4547828

Cited by 27 publications

(4 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, for some 3D applications, the areas of interest can be partially or fully dependent on the depth information [16]. In this context, new research works have been devoted to the application of the RoI feature in the 3D domain [16][17][18][19][20]. In [17], Fan et al proposed a digital watermarking algorithm for copyright protection of 3D images.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Autofocus on Depth of Interest for 3D Image Coding

Samrouth

Déforges

Liu

et al. 2017

Journal of Electrical and Computer Engineering

View full text Add to dashboard Cite

For some 3D applications, one may want to focus on a specific depth zone representing a region of interest in the scene. In this context, we introduce a new functionality called “autofocus” for 3D image coding, exploiting the depth map as an additional semantic information provided by the 3D sequence. The method is based on a joint “Depth of Interest” (DoI) extraction and coding scheme. First, the DoI extraction scheme consists of a precise extraction of objects located within a DoI zone, given by the viewer or deduced from an analysis process. Then, the DoI coding scheme provides a higher quality for the objects in the DoI at the expense of other depth zones. The local quality enhancement supports both higher SNR and finer resolution. The proposed scheme embeds the Locally Adaptive Resolution (LAR) codec, initially designed for 2D images. The proposed DoI scheme is developed without modifying the global coder framework, and the DoI mask is not transmitted, but it is deduced at the decoder. Results showed that our proposed joint DoI extraction and coding scheme provide a high correlation between texture objects and depth. This consistency avoids the distortion along objects contours in depth maps and those of texture images and synthesized views.

show abstract

Section: Introductionmentioning

confidence: 99%

“…The DP-RoI extraction and tracking algorithms were proposed in [18] where Zhang et al exploited the depth information beside the large contrast of illumination in the texture image to extract the RoI. In [19], Karlsson and Sjöström determined the foreground by using the information in the depth map. The foreground was defined as the RoI.…”

Section: Introductionmentioning

confidence: 99%

Autofocus on Depth of Interest for 3D Image Coding

Samrouth

Déforges

Liu

et al. 2017

Journal of Electrical and Computer Engineering

View full text Add to dashboard Cite

show abstract

“…The domain of geometric modeling has also been investigated for the meticulous scenario of multiview, with depth maps being represented as voxel-based octrees [11] or by means of mesh-based coding algorithms [16]. The spatial similarity present in depth images also have been addressed by utilizing staple approaches such as JPEG-2000 and region-ofinterest (ROI) coding algorithms [17]. Interesting results have also been achieved by the employment of region-based techniques [17], however these fell short of feasible implementation due to the extensive bit-rate required to accurately represent the region contours by chain-coding methods [18].…”

Section: Introductionmentioning

confidence: 99%

Efficient multiview depth representation based on image segmentation

Raffaele

Camilleri

Debono

et al. 2012

2012 Picture Coding Symposium

View full text Add to dashboard Cite

Abstract-The persistent improvements witnessed in multimedia production have considerably augmented users demand for immersive 3D systems. Expedient implementation of this technology however, entails the need for significant reduction in the amount of information required for representation. Depth image-based rendering algorithms have considerably reduced the number of images necessary for 3D scene reconstruction, nevertheless the compression of depth maps still poses several challenges due to the peculiar nature of the data. To this end, this paper proposes a novel depth representation methodology that exploits the intrinsic correlation present between colour intensity and depth images of a natural scene. A segmentation-based approach is implemented which decreases the amount of information necessary for transmission by a factor of 24 with respect to conventional JPEG algorithms whilst maintaining a quasi identical reconstruction quality of the 3D views.

show abstract

“…Predominant techniques within the image processing discipline such as JPEG-2000 and region-of-interest (ROI) coding algorithms have been successfully able to take advantage of the spatial similarities present in depth maps [25]. This has lead to accurate results being obtained by employing region-based techniques [26], however, these algorithms were not feasible for implementation due to the extensive amount of data required to represent the region contours by chain-coding techniques [27] and thus lose practical attractiveness when compared to the widely adopted standardized H.264/AVC codec [14]- [16].…”

Section: Introductionmentioning

confidence: 99%

Performance improvement of segmentation-based depth representation in 3D imagery by region merging

Raffaele

Camilleri

Farrugia

et al. 2012

The 2012 International Conference on Advanced Technologies for Communications

View full text Add to dashboard Cite

The feasible implementation of immersive 3D video systems entails the need for a substantial reduction in the amount of image information necessary for representation. Multiview image rendering algorithms based on depth data have radically reduced the number of images required to reconstruct a 3D scene. Nonetheless, the compression of depth maps still poses several challenges due to the particular nature and characteristics of the data. To this end, this paper outlines a depth representation technique, developed in our earlier work, that exploits the correlation intrinsically present between color intensity and depth images capturing a natural scene. In this technique, a segmentation-based algorithm that is backwards compatible with conventional video coding systems is implemented. The effectiveness of our previous technique is enhanced in this contribution by a region merging process on the segmented regions, which results in a decrease in the amount of information necessary for transmission or storage of multiview image data by a factor of 20.5 with respect to the reference H.264/AVC coding methodology. This is furthermore achieved whilst maintaining a 3D image reconstruction and viewing quality which is quasi identical to the referenced approach.peer-reviewe

show abstract

Region-of-Interest 3D Video Coding Based on Depth Images

Cited by 27 publications

References 7 publications

Autofocus on Depth of Interest for 3D Image Coding

Autofocus on Depth of Interest for 3D Image Coding

Efficient multiview depth representation based on image segmentation

Performance improvement of segmentation-based depth representation in 3D imagery by region merging

Contact Info

Product

Resources

About