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Object Based Fast Motion Estimation and Compensation Algorithm for Surveillance Video Compression

첫 페이지 보기
  • 발행기관
    보안공학연구지원센터(IJSIP) 바로가기
  • 간행물
    International Journal of Signal Processing, Image Processing and Pattern Recognition 바로가기
  • 통권
    Vol.7 No.6 (2014.12)바로가기
  • 페이지
    pp.137-148
  • 저자
    Gopal Thapa, Kalpana Sharma, M. K. Ghose
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A239423

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원문정보

초록

영어
In surveillance systems, the storage requirements for video archival are a major concern because of recording of videos continuously for long periods of time, resulting in large amounts of data. Therefore, it is essential to apply efficient compression techniques for compressing surveillance video. The techniques used for the general video compression may not be the efficient technique for the compression of surveillance video because of the use of static camera as compared to moving camera in general purpose videos. Generally surveillance video consist of multiple objects, smaller in size as compared to the background and they have frequents occlusion with each other. In this paper a new object based motion estimation and compensation technique for surveillance video compression is proposed. Background differencing and summing technique (BDST) is used for the segmentation of the moving objects. This technique not only identifies moving object but also the maximum distance moved by the object in given group of frames. A bonding box is created based on the movement of the object in order to segment the moving objects. For exploiting the temporal redundancy, the motion estimation and compensation is carried out for the bonding box region only. The multiresolution property of discrete wavelet transform is used for the motion estimation and compensation. Experimental results show that the approach achieves high compression ratios compared to MPEG-2 compression.

목차

Abstract
 1. Introduction
 2. Moving Object Detection and Segmentation
 3. Object based motion estimation and compensation
 4. Experimental results
 5. Conclusion
 References

키워드

Surveillance video video compression object based motion estimation background image Discrete wavelet transform

저자

  • Gopal Thapa [ Department of Computer Application ]
  • Kalpana Sharma [ Department of Computer Science and Engineering, Sikkim Manipal Institute of Technology ]
  • M. K. Ghose [ Department of Computer Science and Engineering, Sikkim Manipal Institute of Technology ]

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    보안공학연구지원센터(IJSIP) [Science & Engineering Research Support Center, Republic of Korea(IJSIP)]
  • 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 Signal Processing, Image Processing and Pattern Recognition
  • 간기
    격월간
  • pISSN
    2005-4254
  • 수록기간
    2008~2016
  • 십진분류
    KDC 505 DDC 605

이 권호 내 다른 논문 / International Journal of Signal Processing, Image Processing and Pattern Recognition Vol.7 No.6

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