In order to cater to the diversity of terminals and networks, efficient, and flexible adaptation of multimedia content in the delivery path to end consumers is required. To this end, it is necessary to associate the content with metadata that provides the relationship between feasible adaptation choices and various media characteristics obtained as a function of these choices. Furthermore, adaptation is driven by specification of terminal, network, user preference or rights based constraints on media characteristics that are to be satisfied by the adaptation process. Using the metadata and the constraint specification, an adaptation engine can take an appropriate decision for adaptation, efficiently and flexibly. MPEG-21 Part 7 entitled Digital Item Adaptation standardizes among other things the metadata and constraint specifications that act as interfaces to the decision-taking component of an adaptation engine. This paper presents the concepts behind these tools in the standard, shows universal methods based on pattern search to process the information in the tools to make decisions, and presents some adaptation use cases where these tools can be used.

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This paper surveys components that are useful to build programmable, predictable, composable, and scalable multiprocessor-system-on-a-chip (MPSoC) multimedia platforms that can deliver high performance at high power-efficiency. A design-time tool flow is proposed to exploit all forms of parallelism on such platforms. As a first proof of concept, the flow is used to parallelize a relatively simple video standard on a platform consisting of off-the-shelf components. As a second proof of concept, we present the design of a high-performance platform with state-of-theart components. This platform targets real-time H.264 high-definition video encoding at an estimated power consumption of 700 mW.

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One of the key functionalities in today's multimedia applications is streaming. However unlike video, streaming 3D content remains rare, especially for textures. In this paper, we present an intelligent, view dependent approach for streaming and decoding MPEG-4 textures in order to save network and platform resources, while minimizing the perceived quality loss. Different regions of the 3D object's texture are independently decoded up to a desired quality. Whenever viewing conditions change, newly visible texture regions are transmitted and/or already transmitted regions are refined. This 3D view-dependent decoding ofMPEG-4 textures is possible by exploiting the error resilience feature in the MPEG-4 texture-coding tool. It allows a high flexibility (i.e. number of possible quality levels) but at the cost of an increased bitstream size. However, since streaming is possible, the transmission of the bitstream is spread over time, reducing the instantaneous bandwidth and processing cost. INTRODUCI'lONToday, whereas streaming video is common practice, the streaming of 3D content remains rare, if not nonexistent. When decoding and rendering 3D content, the workload on the consumer's platform heavily varies over several orders(o'f magnitude with the viewing conditions [I]. As most!y,only a part of the textured 3D objects is visible at any given time, streaming and/or decoding only the visible regions of the texture will reduce instantaneous bandwidth and/or platform workload. When the viewing conditions change, the newly visible parts can be streamed and/or decoded as they gradually become visible. Consequently, the required network bandwidih as well as the required workload for decoding and rendering textured 3D content are spread over time while minimizing the perceived quality loss. This process is known as view-dependent texture decoding [2]. Figure 1: Principle of view-dependent texture decoding. Non-contiguous portions of the bitstream and associated texture can be independently extracted and rJecoded according to the viewing angle.Within the MPEG-4 multimedia compression standard [3], tools are available for coding 3D content. In particular, MPEG-4 provides a scalable, wavelet based, compression tool for textures, called Visual Texture Coding (VTC) [4]. In this paper, we show how to exploit the error resilience features of VTC for view-dependent texture decoding. VIEW-DEPENDENT TEXTURE DECODINGView-dependent texture decoding is the process of streaming and/or decoding only portions of the bitstream corresponding to a Region of Interest (ROI) in the spatial domain ( Figure 1). The selection of this ROI is based on some viewing conditions, as will be explained in Section 5. View-dependent texture decoding is hence exploits a scalable bitstream in a non-contiguous way. The feasibility of view-dependent texture decoding imposes two constraints to the structure of the bitstream:1. The start of the ROI should easily be identified by the insertion of unique bitstream markers, i.e. a unique bit 0-7803-7402-9/02/$17.00

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