Generalized predictive binary shape coding using polygon approximation

Kim, Jong‐Il; Bovik, Alan C.; Evans, Brian L.

doi:10.1016/s0923-5965(99)00044-2

Cited by 19 publications

(9 citation statements)

References 38 publications

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“…Notice that these families of approaches need a representation of the segmentation or edge information that can have a relevant impact on the total bitrate, for this task efficient contour coding schemes are needed. Typical contour coding techniques rely on chain coding and differential chain coding [12], or on polygon approximation [13]. Even if they are quite effective, these techniques do not exploit the temporal redundancy of contours of the same objects in different time instants or views.…”

Section: Related Workmentioning

confidence: 99%

Depth map coding with elastic contours and 3D surface prediction

Calemme¹,

Zanuttigh²,

Milani³

et al. 2016

2016 IEEE International Conference on Image Processing (ICIP)

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Section: Related Workmentioning

confidence: 99%

Depth map coding with elastic contours and 3D surface prediction

Calemme¹,

Zanuttigh²,

Milani³

et al. 2016

2016 IEEE International Conference on Image Processing (ICIP)

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“…Hence the lossy polygon approximation was developed. Vertices of the spline approximation do not need to be located on the object boundary [24,26]. This polygon representation can be also used for coding shapes in inter mode.…”

Section: Contour-based Shape Codingmentioning

confidence: 99%

“…The publication of the MPEG-4 standard and its work on shape coding [3,26,33] inspired the invention of many shape coding algorithms that are able to outperform MPEG-4 shape coding in terms of coding efficiency while being more computationally demanding. Mainly due to rate distortion optimization, the vertex-based method described in [24] provides an average rate reduction of 7.8% with respect to the content-based arithmetic coder in MPEG-4.…”

Section: Mpeg-4 Shape Codingmentioning

confidence: 99%

Two-Dimensional Shape Coding

Ostermann¹,

Vetro²

2006

Signal Processing and Communications

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content-based storage and retrieval have to allow access to video data based on object descriptions, where objects are described by texture, shape, and motion. Studio and television postproduction applications require editing of video content with objects represented by texture and shape. For collaborative scene visualization like augmented reality, we need to place video objects into the scene. Mobile multimedia applications require content-based interactivity and content-based scalability in order to allocate limited bit rate or limited terminal resources to fit the individual needs. Security applications benefit from content-based scalability as well. All these applications share one common requirement: video content has to be easily accessible on an object basis. MPEG-4 Visual enables this functionality. The main part of this chapter describes MPEG-4 shape coding, the content-based interactivity enabling tool.Given the application requirements, video objects have to be described not only by texture, but also by shape. The importance of shape for video objects has been realized early on by the broadcasting and movie industries employing the so-called chroma-keying technique, which uses a predefined color in the video signal to define the background. Coding algorithms like objectbased analysis-synthesis coding (OBASC) [30| use shape as a parameter in addition to texture and motion for describing moving video objects. Second-generation image coding segments an image into regions and describes each region by texture and shape [28]. The purpose of using shape was to achieve better subjective picture quality, increased coding efficiency as well as an object-based video representation. Two types of VOs are distinguished. For opaque objects, binary shape information is transmitted. Transparent objects are described by gray-scale a-maps defining the outline as well as the transparency variation of an object. MPEG-4 Visual is the first international standard allowing the transmission of arbitrarily shaped video objects (VO) [21 J. Each frame of a VO is called video object plane (VOP

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“…The art of lossy coding method here lies in selecting appropriate contour-pixels, which construct the best fitting polygon to the origin shape-curve. We deploy the approach in [8]: for each polygon side, it is checked whether the approximation of that side and the associated contour segment lies within a tolerance; If not, a new vertex is inserted at the point of largest prediction error, i.e. its distance to the polygon side is farthest; The same evaluation is processed for the 2 newly created polygon sides.…”

Section: Iterative Shape Approximationmentioning

confidence: 99%

Deployment of Constrained Delaunay Mesh in Vop Shape Coding

Tran

Konyha

Enyedi

et al. 2002

Recent Trends in Multimedia Information Processing

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The work presents an alternative method for encoding shape-information of video objects, which is a new requirement in the recent revolution of video codec scheme: compressing and transmitting object-based video streams. The proposed method takes the advantage of the latest development in the video encoding -motion compensation on the base of mesh presentation of frame -to complete its target. The so-called constrained Delaunay mesh is deployed to represent video objects, which are detected from a previous video object detector (in a consistent case of scene, detector can simply function like a segmenting phase of video frame). This special mesh structure in one hand constructs the base for successive motion compensation taking root on mesh-vertices. In another hand, the virtue of constrained property opens a possibility to encode the shape of video object implicitly, therefore it reduces the amount of transmitted information. With constrained Delaunay mesh, shape information of objects is presented with polygon, therefore lossy. The problem can be alleviated by increasing the number of boundary vertices at the cost of bandwidth. The work also puts a stress on controlling this trade-off. Results of integrating the proposed method into a full VOP codec scheme are encouraging.

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Generalized predictive binary shape coding using polygon approximation

Cited by 19 publications

References 38 publications

Depth map coding with elastic contours and 3D surface prediction

Depth map coding with elastic contours and 3D surface prediction

Two-Dimensional Shape Coding

Deployment of Constrained Delaunay Mesh in Vop Shape Coding

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