Camera motion estimation is crucial in video analysis and in object tracking query systems when the motion need to be neutralized before object analysis. In today's ever growing amount of video data provided in compressed formats namely MPEG-1 and MPEG-2, it increasingly makes more sense to perform camera estimation in the compressed domain. Much work has gone into the uncompressed domain, but the time to decompress and analyze is simply too great for population of large video databases. This paper presents a recursive outlier-rejecting least square algorithm for parametric camera estimation in MPEG-1 and MPEG-2 domain. The algorithm has a very low time complexity, results show that it works much faster than real-time playback rate and consumes little system resource. Experiments on synthesized video clips and real world video clips show that the algorithm is effective. Experiments are also none on a large set of real-world video clips to analyze the performance and a query system is built in the process.
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