A multimedia coding standard, MPEG4 has frozen its Committee Draft (CD) as the MPEG4 version 1 CD, last October. It defines Audio-Visual (AV) coding Algorithms and their System Multiplex!Composition formats. Founding ...
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A multimedia coding standard, MPEG4 has frozen its Committee Draft (CD) as the MPEG4 version 1 CD, last October. It defines Audio-Visual (AV) coding Algorithms and their System Multiplex!Composition formats. Founding on Object-base concept, Video part adopts shape coding technology in addition to conventional Texture coding skills. Audio part consists of voice coding tools (HVXC and CELP core) and audio coding tools (HILN and MPEG2 AAC or Twin VQ). Error resilience technologies and Synthetic and Natural Hybrid coding (SNHC) technologies are the MPEG4 specific features. System part defines flexible Multiplexing of audio-visual bit-streams and Scene Composition for user-interactive reconstruction of the scenes at decoder side. The version 1 standardization will be finalized in 1998, with some possible minute changes. The expected application areas are real-time communication, mobile multimedia, internet/intranet accessing, broadcasting, storage media, surveillance, and so on.
作者：
Jang, ESHanyang Univ
Coll Informat & Commun Software Div Seoul 133791 South Korea
Although frame-based MPEG-4 video services have been successfully deployed since 2000, MPEG-4 video coding is now facing great competition in becoming a dominant player in the market. Object-based coding is one of the...
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Although frame-based MPEG-4 video services have been successfully deployed since 2000, MPEG-4 video coding is now facing great competition in becoming a dominant player in the market. Object-based coding is one of the key functionalities of MPEG-4 video coding. Real-time object-based video encoding is also important for multimedia broadcasting for the near future. Object-based video services using MPEG-4 have not yet made a successful debut due to several reasons. One of the critical problems is the coding complexity of object-based video coding over frame-based video coding. Since a video object is described with an arbitrary shape, the bitstream contains not only motion and texture data but also shape data. This has introduced additional complexity to the decoder side as well as to the encoder side. In this paper, we have analyzed the current MPEG-4 video encoding tools and proposed efficient coding technologies that reduce the complexity of the encoder. Using the proposed coding schemes, we have obtained a 56 percent reduction in shape-coding complexity over the MPEG-4 video reference software (Microsoft version, 2000 edition).
In a rectangular-block division-based coding method, there is a problem that, in the blocks where different regions coexist, the coding efficiency decreases. In the segmentation-based coding method, which is promising...
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Visual shape perception is central to many everyday tasks, from object recognition to grasping and handling tools.1-10 Yet how shape is encoded in the visual system remains poorly understood. Here, we probed shape rep...
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Visual shape perception is central to many everyday tasks, from object recognition to grasping and handling tools.1-10 Yet how shape is encoded in the visual system remains poorly understood. Here, we probed shape representations using visual aftereffects-perceptual distortions that occur following extended exposure to a stimulus.11-17 Such effects are thought to be caused by adaptation in neural populations that encode both simple, low-level stimulus characteristics17-20 and more abstract, high-level object features.21-23 To tease these two contributions apart, we used machine -learning methods to synthesize novel shapes in a multidimensional shape space, derived from a large database of natural shapes.24 Stimuli were carefully selected such that low-level and high-level adaptation models made distinct predictions about the shapes that observers would perceive following adaptation. We found that adaptation along vector trajectories in the high-level shape space predicted shape aftereffects better than simple low-level processes. Our findings reveal the central role of high-level statistical features in the visual representation of shape. The findings also hint that human vision is attuned to the distribution of shapes experienced in the natural environment.
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