Evaluation of pixel- and motion vector-based global motion estimation for camera motion characterization

Pixel-based and motion vector-based global motion estimation (GME) techniques are evaluated in this paper with an automatic system for camera motion characterization. First, the GME techniques are compared with a frame-by-frame PNSR measurement using five video sequences. The best motion vector-based GME method is then evaluated together with a common and a simplified pixel-based GME technique for camera motion characterization. For this, selected unedited videos from the TRECVid 2005 BBC rushes corpus are used. We evaluate how the estimation accuracy of global motion parameters affects the results for camera motion characterization in terms of retrieval measures. The results for this characterization show that the simplified pixel-based GME technique obtains results that are comparable with the common pixel-based GME method, and outperforms significantly the results of an earlier proposed motion vector-based GME approach.