DocumentCode
39443
Title
Detecting Motion through Dynamic Refraction
Author
Alterman, M. ; Schechner, Y.Y. ; Perona, Pietro ; Shamir, J.
Author_Institution
Dept. of Electr. Eng., Technion - Israel Inst. of Technol., Haifa, Israel
Volume
35
Issue
1
fYear
2013
fDate
Jan. 2013
Firstpage
245
Lastpage
251
Abstract
Refraction causes random dynamic distortions in atmospheric turbulence and in views across a water interface. The latter scenario is experienced by submerged animals seeking to detect prey or avoid predators, which may be airborne or on land. Man encounters this when surveying a scene by a submarine or divers while wishing to avoid the use of an attention-drawing periscope. The problem of inverting random refracted dynamic distortions is difficult, particularly when some of the objects in the field of view (FOV) are moving. On the other hand, in many cases, just those moving objects are of interest, as they reveal animal, human, or machine activity. Furthermore, detecting and tracking these objects does not necessitate handling the difficult task of complete recovery of the scene. We show that moving objects can be detected very simply, with low false-positive rates, even when the distortions are very strong and dominate the object motion. Moreover, the moving object can be detected even if it has zero mean motion. While the object and distortion motions are random and unknown, they are mutually independent. This is expressed by a simple motion feature which enables discrimination of moving object points versus the background.
Keywords
atmospheric turbulence; feature extraction; image motion analysis; object detection; object tracking; refraction; FOV; atmospheric turbulence; attention-drawing periscope; dynamic refraction; field of view; motion detection; motion feature; moving object point discrimination; object detection; object tracking; random dynamic distortions; water interface; Animals; Cameras; Covariance matrix; Dynamics; Nonlinear distortion; Optical distortion; Vectors; Motion detection; classification; distortion; random media; refraction; Algorithms; Artifacts; Artificial Intelligence; Image Interpretation, Computer-Assisted; Motion; Pattern Recognition, Automated; Refractometry;
fLanguage
English
Journal_Title
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher
ieee
ISSN
0162-8828
Type
jour
DOI
10.1109/TPAMI.2012.192
Filename
6296664
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