This paper presents an object-based layered video coding scheme which achieves very high compression efficiency along with the provision for advanced content-based functionalities, e.g., content-based scalability or c...
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This paper presents an object-based layered video coding scheme which achieves very high compression efficiency along with the provision for advanced content-based functionalities, e.g., content-based scalability or content-based access and manipulation of video data. In a first step, a video sequence is segmented into several arbitrarily shaped ''object layers.'' To achieve the desired content-based functionalities, a baseline shape-adaptive discrete cosine transform (DCT) coding algorithm is introduced which can be seen as an extension of conventional block-based DCT coding schemes (e.g., H.261, H.263, MPEG-1, or MPEG-2) toward coding of arbitrarily shaped image content, In order to increase compression efficiency, the baseline object-based layered approach can be extended with an object-based motion prediction toolbox. Using this toolbox, the coding scheme can potentially select specific prediction techniques for every object layer to be coded. To illustrate the concept, an extension of the baseline shape-adaptive DCT algorithm with a technique for global background motion estimation and compensation is described which significantly improves the compression efficiency of suitable video sequences compared to standard MPEG coding schemes.
Video multicast is a challenging problem due to the heterogeneous and best-effort nature of the Internet. In this paper, we present a novel video multicast framework that exploits the potential of object scalability o...
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Video multicast is a challenging problem due to the heterogeneous and best-effort nature of the Internet. In this paper, we present a novel video multicast framework that exploits the potential of object scalability offered by MPEG-4. Specifically, we introduce the concept of object transmission proxy (OTP), which filters incoming streams using object-based bandwidth adaptation to meet dynamic network conditions. Multiple OPTs can form an overlay network that interconnects diverse multicast islands with semi-uniform demands within each single island. We concur with the wisdom that an application best knows the utility of its data. Hence, the bandwidth-adaptation algorithm for the OTPs adaptively allocates bandwidth among video objects according to their respective utilities and then performs application-level filtering based on an effective stream classification and packetization scheme. Extensive simulation results demonstrate that our framework has substantial performance improvement over conventional bandwidth-adaptation schemes. It is particularly suitable for object-based video multicasting where the objects are of different importance.
We propose a scheme for coding subregions in video scenes to provide content-based scalable video. For each region, a special color is used to represent the nonobject area, and the resulting frames are coded using con...
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We propose a scheme for coding subregions in video scenes to provide content-based scalable video. For each region, a special color is used to represent the nonobject area, and the resulting frames are coded using conventional video coding algorithms. At the decoder, the region shape is recovered based on chroma keying, and hence, content-based manipulations are made possible. A number of techniques that eliminate boundary artifacts common to region-based coding are presented. In this scheme, no explicit shape coding is needed, and advantages of existing coding algorithms are retained. This scheme was submitted to ISO MPEG-4 and performed very well in the subjective tests.
In this work, we investigate a new class of scalable image coders. We target at the same time multiresolution (for spatial scalability), critical (for compression efficiency) and (hierarchical) segmentation based deco...
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ISBN:
(纸本)0819437034
In this work, we investigate a new class of scalable image coders. We target at the same time multiresolution (for spatial scalability), critical (for compression efficiency) and (hierarchical) segmentation based decompositions (for object based scalability). Hierarchical segmentation allows to access the description of a scene in terms of regions or objects at several resolution levels, and thus encode and transmit the objects selectively. From a coding viewpoint, it is obviously interesting to couple the multi-level segmentation with a critically decimated decomposition of the image (to avoid redundancy of representation). However, the association of object representation combined with critically sampled multiresolution decomposition has not been studied to our knowledge. In this paper, we propose new methods to perform hierarchical segmentation of an image using critically decimated non linear filter banks;the resulting decomposition embeds a hierarchical segmentation map and is therefore particularly well suited for region based coding and progressive transmission. As the segmentation map is embedded by reconstruction inside the decomposition, we do not really need to transmit it separately thus attempting to reduce the bitrate. Simulations show that a prototype coder of this type has a degradation in terms of rate/distortion tradeoff compared to a conventional wavelet based image coder, but offers in addition new perspectives for object based manipulations, coding and transmission.
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