A new object-oriented approach for video compression at very low bit rate

Object-oriented approaches have been proposed for coding video sequences at very low bit rate. Typically, object-oriented coding algorithms segment each image into regions of uniform motion and estimate motion of these regions to generate more accurate motion compensated images. Due to the iterative computing of complex motion models´ parameters, the computational complexity of object-oriented algorithms is often high. The present author gives a two-stage algorithm for motion field segmentation and estimation in an object-oriented coder whose computational complexity is reduced by delaying the use of complex motion models at the end of the proposed algorithm. In the first stage of the algorithm, a standard block-matching algorithm and a maximum a posteriori probability estimate are used to compute a translational motion field and its segmentation. That segmentation is then utilized in the second stage to estimate the parameters of complex motion models. Compared to standard block-based algorithms, simulation results show that the proposed algorithm significantly reduces the bit rate needed to encode video sequences and is appropriate for very low bit rate applications