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Detecting Motion through Dynamic Refraction
Jan. 2013 (vol. 35 no. 1)
pp. 245-251
M. Alterman, Dept. of Electr. Eng., Technion - Israel Inst. of Technol., Haifa, Israel
Y. Y. Schechner, Dept. of Electr. Eng., Technion - Israel Inst. of Technol., Haifa, Israel
P. Perona, Dept. of Electr. Eng., California Inst. of Technol., Pasadena, CA, USA
J. Shamir, Dept. of Electr. Eng., Technion - Israel Inst. of Technol., Haifa, Israel
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.
Index Terms:
refraction,atmospheric turbulence,feature extraction,image motion analysis,object detection,object tracking,moving object point discrimination,motion detection,dynamic refraction,random dynamic distortions,atmospheric turbulence,water interface,attention-drawing periscope,field of view,FOV,object detection,object tracking,motion feature,Optical distortion,Cameras,Nonlinear distortion,Covariance matrix,Dynamics,Animals,Vectors,distortion,Motion detection,refraction,random media,classification
Citation:
M. Alterman, Y. Y. Schechner, P. Perona, J. Shamir, "Detecting Motion through Dynamic Refraction," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 35, no. 1, pp. 245-251, Jan. 2013, doi:10.1109/TPAMI.2012.192
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