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Detecting and tracking multiple moving objects using temporal integration

  • Michal Irani
  • Benny Rousso
  • Shmuel Peleg
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 588)

Abstract

Tracking multiple moving objects in image sequences involves a combination of motion detection and segmentation. This task can become complicated as image motion may change significantly between frames, like with camera vibrations. Such vibrations make tracking in longer sequences harder, as temporal motion constancy can not be assumed.

A method is presented for detecting and tracking objects, which uses temporal integration without assuming motion constancy. Each new frame in the sequence is compared to a dynamic internal representation image of the tracked object. This image is constructed by temporally integrating frames after registration based on the motion computation. The temporal integration serves to enhance the region whose motion is being tracked, while blurring regions having other motions. These effects help motion analysis in subsequent frames to continue tracking the same motion, and to segment the tracked region.

Keywords

Optical Flow Motion Analysis Motion Parameter Temporal Integration Motion Computation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • Michal Irani
    • 1
  • Benny Rousso
    • 1
  • Shmuel Peleg
    • 1
  1. 1.Dept. of Computer ScienceThe Hebrew University of JerusalemJerusalemIsrael

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