The current model for multicast transmission of video over the Internet assumes that a fixed average bandwidth is uniformly present throughout the network. Consequently, sources limit their transmission rates to accommodate the lowest bandwidth links, even though high-bandwidth connectivity might be available to many of the participants. We propose an architecture where a video transmission can be decomposed into multiple sessions with different bandwidth requirements using an application-level gateway. Our video gateway transparently connects pairs of sessions into a single logical conference by manipulating the data and control information of the video streams. In particular, the gateway performs bandwidth adaptation through transcoding and rate-control. We describe an efficient algorithm for transcoding Motion-JPEG to H.261 that runs in real-time on standard workstations. By making the Real-time Transport Protocol (RTP) an integral component of our architecture, the video gateway in...

Many advanced video applications require manipulations of compressed video signals. Popular video manipulation functions include overlap (opaque or semi-transparent), translation, scaling, linear filtering, rotation, and pixel multiplication. In this paper, we propose algorithms to manipulate compressed video in the compressed domain. Specifically, we focus on compression algorithms using the Discrete Cosine Transform (DCT) with or without Motion Compensation (MC). Compression systems of such kind include JPEG, Motion JPEG, MPEG, and H.261. We derive a complete set of algorithms for all aforementioned manipulation functions in the transform domain, in which video signals are represented by quantized transform coefficients. Due to a much lower data rate and the elimination of decompression/compression conversion, the transform-domain approach has great potential in reducing the computational complexity. The actual computational speedup depends on the specific manipulation functions and ...

We present a neural network-based frontal face detection system, which is completely implemented in the compressed domain. The features used for this purpose are the DCT components of Y, Cr and Cb available from the compressed data of I-frames in MPEG videos. Since DCT coefficients captures frame information concisely, use of DCT features reduces the complexity of the neural network used in the algorithm. In addition, it increases the computational efficiency. The data is used in two stages: in the first stage, a skin color filter, based on Cr and Cb DCT information, is used to locate skin regions. In the second stage, a 4×4 blocks sized window is used to scan the skin regions in the compressed domain image to extract Y-DCT features. A neural network then is trained using these DCT features to classify patterns as faces or non-faces. The preliminary results obtained are encouraging enough to continue research in this direction. 1.

An enduring trait of the Internet is its heterogeneity. Evidence of this heterogeneity includes the wide range of network transmission rates, varying across many orders of magnitude, and the vast differences in computing power, ranging from PDA's to supercomputers. These heterogeneities present significant barriers to the transmission of real-time multimedia data across groups. The barriers stem from the fact that in order to accommodate the entire gamut of group member characteristics, e.g., bandwidth availability or computing power, a source is required to transmit its data with properties matching the most constrained receiver. Instead, we would like to transmit media to multiple receivers at heterogeneous rates and properties tha...

Multi-point network video services require compositing several video sources into a single displayed video stream. Compositing video directly in the compressed domain can save computations by processing less data and avoiding the conversion process back and forth between the compressed and uncompressed data formats. Earlier work has demonstrated the computational speedup of compositing DCT-compressed video directly in the DCT domain, compared to the straightforward spatial-domain approach. Typical compositing operations include overlapping, scaling, translation, filtering, etc. In this paper, we propose a new decoding algorithm for MC-DCT compressed video which converts MC-DCT compressed video to the DCT domain and enables video compositing in the DCT compressed domain. Computational complexity is analyzed. The idea of network compositing and its impacts on multimedia network implementations are also discussed.

used to process each individual video object or to combine multiple video 166 objects into a single composited scene. Although the definition of compositing functions does not rely on the structured video model, we can represent video compositing functions in an efficient and hierarchical way based on the structured video concept. In particular, we described several possible data structures for representing video compositing functions: time-varying scripts, expressions, ordered lists, and trees. The first three structures are independent of final specific implementations and are on a higher abstract level than the last one. The tree structure, however, has closer correspondence with practical implementations. The structured video model has both advantages and disadvantages. By keeping the video objects in a video scene logically separate along the path from the source to the final destination, various characteristics of user and service requirements ca

The two-dimensional discrete cosine transform (2-D DCT) and its subsequent quantization are widely used in standard video encoders. However, since most DCT coefficients become zeros after quantization, a number of redundant computations are performed. This paper proposes a hybrid statistical model used to predict the zeroquantized DCT (ZQDCT) coefficients for intratransform and to achieve better real-time performance. First, each pixel block at the input of DCT is decomposed into a series of mean values and a residual block. Subsequently, a statistical model based on Gaussian distribution is used to predict the ZQDCT coefficients of the residual block. Then, a sufficient condition under which each quantized coefficient becomes zero is derived from the mean values. Finally, a hybrid model to speed up the DCT and quantization calculations is proposed. Experimental results show that the proposed model can reduce more redundant computations and achieve better real-time performance than the reference in the literature at the cost of negligible video quality degradation. Experiments also show that the proposed model significantly reduces multiplications for DCT and quantization. This is particularly suitable for processors in portable devices where multiplications consume more power than additions. Computational reduction implies longer battery lifetime and energy economy. Copyright © 2008 Jin Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 1.