Model-based error concealment for wireless video
We introduce model-based schemes for error concealment of networked video. We build appearance models for specific objects in the scene and use these models to replenish any lost information. Due to the models being designed specifically for the object, they are able to capture the statistical variations in the object appearance more effectively, thereby leading to better error-concealment performance. We examine statistical modeling techniques from the literature and introduce a new efficient and accurate linear model for data representation, called the mixture of principal components (MPC), and use these models for error concealment. We simulate lossy network conditions and show that these model-based concealment schemes outperform traditional concealment schemes across a variety of loss probabilities and bit rates for the coded video.