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An Enriched 3D Trajectory Generated Equations for the Most Common Path of Multiple Object Tracking

첫 페이지 보기
  • 발행기관
    보안공학연구지원센터(IJMUE) 바로가기
  • 간행물
    International Journal of Multimedia and Ubiquitous Engineering SCOPUS 바로가기
  • 통권
    Vol.10 No.6 (2015.06)바로가기
  • 페이지
    pp.53-76
  • 저자
    Israa Hadi, Mustafa Sabah
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A251298

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원문정보

초록

영어
Object tracking is important and challenging task in many computer vision applications such as surveillance, vehicle navigation, and autonomous robot navigation. Video surveillance in a dynamic environment, especially for humans and vehicles, is one of the current challenging research topics in computer vision. It is a key technology to fight against terrorism, crime, public safety and for efficient management of traffic. In this paper, in order To get an accurate description of the trajectory points, regression analysis technique is used. This technique has the ability to summarize the collection of trajectory points by fitting it to mathematical models which will accurately describe these points and consequently describe object behavior. The regression analysis technique uses the least square method to obtain the best fit of equations for the given set of trajectory points. The least square method assumes that the best fit curve has the minimal sum of the deviations squared error from the given set of data. In this paper, propose new method to deal with the trajectory by converting the trajectory points into 3D approximation function using best fit plane after interpolation the time factor this method offers high flexibility as well as statistical tools for the analysis behavior of object. Planar regression calculates the best fit plane through a group of 3 or more data points. The plane is calculated by minimizing the residuals (or errors) between the plane and the original points using least squares minimization. The objective of this paper was to develop methods for optimization of least square best fit geometry for planes.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Least Squares Method
 4. Curve Fitting
 5. Linear Regression
 6. Cat Swarm Optimization (CSO)
  6.1. Seeking Mode: Resting and Observing
  6.2 Tracing Mode: Running After a Target
 7. Parallel Cat Swarm Optimization (PCSO)
  7.1 Parallel Tracing Mode Process
  7.2 Information Exchanging Process
 8. Average-Inertia Weighted Cat Swarm Optimization (AICSO)
 9. Fitness Approximation Method
  9.1 Updating the Individual Database
  9.2 Fitness Calculation Strategy
 10. Proposed Algorithm
  10.1 Multi –Part Object Representation
  10.2 The Search Algorithm
  10.3. Curve Fitting
  10.4 The Main Algorithm
 11. Simulation Results
 12. Conclusion
 References

저자

  • Israa Hadi [ Professor College of Information Technology University of Babylon, Israa ] First author
  • Mustafa Sabah [ Ph.D. Student, College of Information Technology University of Babylon ] Corresponding Author

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    보안공학연구지원센터(IJMUE) [Science & Engineering Research Support Center, Republic of Korea(IJMUE)]
  • 설립연도
    2006
  • 분야
    공학>컴퓨터학
  • 소개
    1. 보안공학에 대한 각종 조사 및 연구 2. 보안공학에 대한 응용기술 연구 및 발표 3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최 4. 보안공학 기술의 상호 협조 및 정보교환 5. 보안공학에 관한 표준화 사업 및 규격의 제정 6. 보안공학에 관한 산학연 협동의 증진 7. 국제적 학술 교류 및 기술 협력 8. 보안공학에 관한 논문지 발간 9. 기타 본 회 목적 달성에 필요한 사업

간행물

  • 간행물명
    International Journal of Multimedia and Ubiquitous Engineering
  • 간기
    월간
  • pISSN
    1975-0080
  • 수록기간
    2008~2016
  • 등재여부
    SCOPUS
  • 십진분류
    KDC 505 DDC 605

이 권호 내 다른 논문 / International Journal of Multimedia and Ubiquitous Engineering Vol.10 No.6

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