Real-time object tracking using multi-res. critical points filters

Jérôme Durand, Seth Hutchinson

Research output: Contribution to journalConference article

Abstract

In this paper, we will propose a new method for object tracking, which is primarily based on the results from prof. Shinagawa's image matching. We will provide a method that tracks an object and follows it in real-time through a sequence of images which are given, for example, by a robotic camera. The main feature of the method is that it is not affected by the movements (within a certain reasonable range) of the camera or the object; such as, translation, rotation or scaling. The algorithm is also insensible to regular changes of the object's shape. For real-time applications, the algorithm allows the tracking of an object through sequence of 64*64 images, at a rate of over 8 frames/second.

Original languageEnglish (US)
Pages (from-to)1682-1687
Number of pages6
JournalProceedings - IEEE International Conference on Robotics and Automation
Volume2
StatePublished - Dec 9 2003
Event2003 IEEE International Conference on Robotics and Automation - Taipei, Taiwan, Province of China
Duration: Sep 14 2003Sep 19 2003

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Real-time object tracking using multi-res. critical points filters'. Together they form a unique fingerprint.

  • Cite this