In this paper, we present an improved approach to predictive video decoding based on global and local motion
reliability. The framework consists of three processing stages. Global motion (GM) estimation and motion reliability
analysis are the key components in the first stage, where we model global motion and refine the MV field. In the second
stage, we predict local and global motion for the target frame, and determine corresponding weights based on the Linear
Minimum Mean Square Error (LMMSE) criterion. Finally in the third stage, a temporal interpolator is applied to
compose two future frames, which are linearly combined to form the final predicted frame. Our results indicate the
proposed method achieves better visual quality compare to other state-of-the-art predictive decoding approaches,
particularly in sequences involving moving camera and objects.
In this text we present a system for streaming video content encoded using the motion-compensated Embedded Zero Block Coder (EZBC). The system incorporates unequal loss protection in the form of multiple description FEC (MD-FEC) coding, which provides adequate protection for the embedded video bitstream when the loss process is not very bursty. The adverse effects of burst losses are reduced using a novel motion-compensated error concealmet method.
In this paper we present a method of creating domain-based multiple descriptions of images and video. Descriptions are created by partitioning the domain of the signal into sets whose points are maximally separated from each other. This property enables simple error concealment methods to produce good estimates of lost signal samples. We present the approach in the context of Internet transmission of subband-coded images and scalable motion compensated 3-D subband-coded video, but applications are not limited to these scenarios.