Real-time robust 3D object tracking and estimation for surveillance system

hyung H. Park, Seungmin Rho, Chang-Sung Jeong

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

We present a new 3D object tracking algorithm that supports multiple planar and nonplanar objects with real-time processing speed and high accuracy. The main problem of object tracking algorithm is the limitation of the supporting type of target object, slow processing speed, and low tracking accuracy. Our algorithm provides high accuracy and real-time performance while detecting not only planar objects but also nonplanar objects. The real-time performance is accomplished by using Features from Accelerated Segment Test corner detection, region of interest, and parallel processing on a multicore processor. High accuracy is realized by using a scale-invariant feature transform descriptor, random sample consensus, region of interest, and double robust filtering.

Original languageEnglish
Pages (from-to)1599-1611
Number of pages13
JournalSecurity and Communication Networks
Volume7
Issue number10
DOIs
Publication statusPublished - 2014 Jan 1

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ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems

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Real-time robust 3D object tracking and estimation for surveillance system. / Park, hyung H.; Rho, Seungmin; Jeong, Chang-Sung.

In: Security and Communication Networks, Vol. 7, No. 10, 01.01.2014, p. 1599-1611.

Research output: Contribution to journalArticle

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