sequence_alignment - Alignment of Non-Overlapping Sequences...

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Alignment of Non-Overlapping Sequences Yaron Caspi Michal Irani Dept. of Computer Science and Applied Math The Weizmann Institute of Science 76 100 Rehovot, Israel This paper shows how two image sequences that have no spatial overlap between their$elds of view can be aligned both in time and in space. Such alignment is possible when the two cameras are attached closely together and are moved jointly in space. The common motion induces “similar changes over time within the two sequences. This correlated temporal behaviol; is used to recover the spatial and temporal transformations between the two sequences. The requirement of “coherent appearance” in standard im- age alignment techniques is therefore replaced by “coherent temporal behavior”, which is often easier to satisb. This approach to alignment can be used not only for aligning non-overlapping sequences, but also for handling other cases that are inherently dificult for standard im- age alignment techniques. We demonstrate applications of this approach to three real-world problems: (i) alignment of non-overlapping sequences for generating wide-screen movies, (ii) alignment of images (sequences) obtained at sign$cantly different zooms, for surveillance applications, and, (iii) multi-sensor image alignment for multi-sensor fir- sion. 1 Introduction The problem of image alignment (or registration) has been extensively researched, and successful approaches have been developed for solving this problem. Some of these approaches are based on matching extracted local im- age features. Other approaches are based on directly match- ing image intensities. A review of some of these meth- ods can be found in [ 191 and [ 131. However, all these ap- proaches share one basic assumption: that there is sufficient overlap between the two images to allow extraction of com- mon image properties, namely, that there is sufficient “sim- ilarity” between the two images (“Similarity” of images is used here in the broadest sense. It could range from gray- level similarity, to feature similarity, to similarity of fre- quencies, and all the way to statistical similarity such as mu- tual information [21]). In this paper the following question is addressed: Can two images be aligned when there is very little similarity be- tween them, or even more extremely, when there is no spatial overlap ut all between the two images? When dealing with individual images, the answer tends to be “No”. However, this is not the case when dealing with image sequences. An image sequence contains much more information than any individual frame does. In particular, temporal changes (such as dynamic changes in the scene, or the induced image mo- tion) are encoded between video frames, but do not appear in any individual frame. Such information can form a pow- erful cue for alignment of two (or more) sequences. Caspi and Irani [6] and Stein [ 181 have illustrated an applicabil- ity of such an approach for aligning two sequences based on common dynamic scene information. However, they as- sumed that the same temporal. changes in the scene (e.g.,
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This note was uploaded on 06/13/2011 for the course CAP 6412 taught by Professor Staff during the Spring '08 term at University of Central Florida.

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sequence_alignment - Alignment of Non-Overlapping Sequences...

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