We propose measures to evaluate the performance of video object segmentation and tracking methods quantitatively without
ground-truth segmentation maps. The proposed measures are based on
spatial differences of color and motion along the boundary of the
estimated video object plane and temporal differences between the
color histogram of the current object plane and its neighbors.
They can be used to localize (spatially and/or temporally) regions
where segmentation results are good or bad; and/or combined to
yield a single numerical measure to indicate the goodness of the
boundary segmentation and tracking results over a sequence. The
validity of the proposed performance measures without ground
truth have been demonstrated by canonical correlation analysis of
the proposed measures with another set of measures it with
ground-truth on a set of sequences (where ground truth
information is available). Experimental results are presented to
evaluate the segmentation maps obtained from various sequences
using different segmentation and tracking algorithms.
This paper introduces a novel method for subpixel accuracy stabilization of unsteady digital films and video sequences. The proposed method offers a near-closed-form solution to the estimation of the global subpixel displacement between two frames, that causes the misregistration of them. The criterion function used is the mean-squared error over the displaced frames, in which image intensities at subpixel locations are evaluated using bi-linear interpolation. The proposed algorithm is both faster and more accurate than the search-based solutions found in the literature. Experimental results demonstrate the superiority of the proposed method to the spatio-temporal differentiation and surface fitting algorithms, as well. Furthermore, the proposed algorithm is designed so that it is insensitive to frame-to-frame intensity variations. It is also possible to estimate any affine motion between two frames by applying the proposed algorithm on three non-collinear points in the unsteady frame.
The effect of image stabilization on the performance of the MPEG-2 video coding algorithm is investigated. It is shown that image stabilization prior to MPEG-2 coding of an unsteady image sequence does increase the quality of the compressed video considerably. The quality improvement is explained by fact that an actual zero motion vector is favored over a zero differential motion vector in the MPEG-2 video coding scheme. The bits saved in coding the motion information in P frames are then utilized in the coding of the DCT data in I frames. The temporal prediction of the macroblocks in P and B frames are also improved because of the increased quality of the compressed I frames and because an image stabilization algorithm can compensate for displacement with better than 1/2 pixel accuracy.
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