Feature-based error concealment for object-based video

In this paper, a new error concealment algorithm for MPEG-4 object-based video is presented. The algorithm consists of a feature matching step to identify temporally corresponding features between video frames and an affine parameter estimation step to find the motion of the feature points. In the feature matching step, an efficient cross-radial search (CRS) method is developed to find the best matching points. In the affine parameter estimation step, a non-iterative least squares estimation algorithm is developed to estimate the affine parameters. An attractive feature of the algorithm is that the shape data and texture data are handled by the same method. Unlike previous methods, this unified approach works for the case where the video object undergoes a drastic movement, such as a sharp turn. Experimental results show that the proposed algorithm performs much better than previous approaches by about 0.3-2.8 dB for shape data and 1.6-5.0 dB for texture data.