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Shade Interest Points for Dynamic Stream Object Categorization

첫 페이지 보기
  • 발행기관
    보안공학연구지원센터(IJMUE) 바로가기
  • 간행물
    International Journal of Multimedia and Ubiquitous Engineering SCOPUS 바로가기
  • 통권
    Vol.10 No.4 (2015.04)바로가기
  • 페이지
    pp.63-70
  • 저자
    S. Suresh Babu, Venkata Naresh Mandhala, Siva Koteswara Rao Chinnam, Tai-hoon Kim
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A245330

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원문정보

초록

영어
Discovery of investment focuses for ensuing handling is one of the fundamental parts of machine vision. Object order of pictures vigorously depends on investment point identification from which nearby picture descriptors are registered for picture matching. Since investment focuses are focused around luminance, past methodologies generally overlooked the color viewpoint. Later an approach that uses saliency-based peculiarity determination improved by a primary part dissection based scale choice strategy is created. It is utilized to lessen the affectability to changing imaging conditions, and hence it is a light-invariant investment point's location framework. Utilization of color expands the uniqueness of investment focuses. In the setting of item distinguishment, the human observation framework is regularly pulled in by contrasts between parts of pictures and by movement or moving articles. In this manner, in the feature indexing system, investment focuses give more helpful data when contrasted with static pictures. So we propose to amplify the above methodology for element feature streams utilizing Space-Time Interest Points (Stips) that uses a calculation for scale adaption of spatio-worldly investment focuses. STIP distinguishes moving questions in features and describes some particular changes in the development of these articles. A handy execution of the proposed framework accepts our case to help element streams and further it could be utilized as a part of uses, for example, Motion Tracking, Entity Detection and Naming applications.

목차

Abstract
 1. Introduction
 2. Background Work
 3. Proposed Approach
 4. Performance Evaluation
 5. Conclusion
 References

키워드

Interest point calculation Space-Time Interest Points Machine Vision

저자

  • S. Suresh Babu [ Information Technology Department, VFSTR University, Vadlamudi-522213, Guntur, India ]
  • Venkata Naresh Mandhala [ Information Technology Department, VFSTR University, Vadlamudi-522213, Guntur, India ]
  • Siva Koteswara Rao Chinnam [ Information Technology Department, VFSTR University, Vadlamudi-522213, Guntur, India ]
  • Tai-hoon Kim [ Department of Convergence Security, Sungshin Women's University, 249-1, Dongseon-dong 3-ga, Seoul, 136-742, Korea ] 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.4

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