Sequence-to-Sequence
Alignment
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Paper Abstract:
This paper presents an approach for establishing correspondences in time
and in space between two different video sequences of the same dynamic
scene, recorded by stationary uncalibrated video cameras. The method simultaneously
estimates both spatial alignment as well as temporal synchronization
(temporal alignment) between the two sequences, using all available spatio-temporal
information. 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.
We also present a ``direct'' method for sequence-to-sequence alignment.
The algorithm simultaneously estimates spatial and temporal alignment parameters
directly from measurable sequence quantities, without requiring prior estimation
of point correspondences, frame correspondences, or moving object detection.
Results are shown on real image sequences taken by multiple video cameras.
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