Detecting motion through dynamic refraction

Marina Alterman, Yoav Y. Schechner, Pietro Perona, Joseph Shamir

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Article number6296664
Pages (from-to)245-251
Number of pages7
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Volume35
Issue number1
DOIs
StatePublished - 2013

Keywords

  • Motion detection
  • classification
  • distortion
  • random media
  • refraction

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics

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