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Issue No.11 - November (2002 vol.24)
pp: 1409-1424
ABSTRACT
<p><b>Abstract</b>—This paper studies the problem of sequence-to-sequence alignment, namely, establishing correspondences in <it>time</it> and in <it>space</it> between two different video sequences of the same dynamic scene. The sequences are recorded by uncalibrated video cameras which are either stationary or jointly moving, with fixed (but unknown) internal parameters and relative intercamera external parameters. Temporal variations between image frames (such as moving objects or changes in scene illumination) are powerful cues for alignment, which cannot be exploited by standard image-to-image alignment techniques. We show that, by folding spatial and temporal cues into a single alignment framework, situations which are inherently ambiguous for traditional image-to-image alignment methods, are often uniquely resolved by sequence-to-sequence alignment. Furthermore, the ability to align and integrate information across multiple video sequences both in <it>time</it> and in <it>space</it> gives rise to new video applications that are not possible when only image-to-image alignment is used.</p>
INDEX TERMS
Sequence-to-sequence alignment, space-time analysis, direct methods, feature-based methods.
CITATION
Yaron Caspi, Michal Irani, "Spatio-Temporal Alignment of Sequences", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.24, no. 11, pp. 1409-1424, November 2002, doi:10.1109/TPAMI.2002.1046148
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