Journal of the Korea Institute of Information and Communication Engineering (한국정보통신학회논문지)

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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A Descriptor Design for the Video Retrieval Combining the Global Feature of an Image and the Local of a Moving Object

영상의 전역 특징과 이동객체의 지역 특징을 융합한 동영상 검색 디스크립터 설계

  • Jung, Byung-Man (Information and Communications Engineering, Daejeon University) ;
  • Lee, Kyu-Won (Information and Communications Engineering, Daejeon University)
  • Received : 2013.09.03
  • Accepted : 2013.10.15
  • Published : 2014.01.31
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Abstract

A descriptor which is suitable for motion analysis by using the motion features of moving objects from the real time image sequence is proposed. To segment moving objects from the background, the background learning is performed. We extract motion trajectories of individual objects by using the sequence of the 1st order moment of moving objects. The center points of each object are managed by linked list. The descriptor includes the 1st order coordinates of moving object belong to neighbor of the pre-defined position in grid pattern, The start frame number which a moving object appeared in the scene and the end frame number which it disappeared. A video retrieval by the proposed descriptor combining global and local feature is more effective than conventional methods which adopt a single feature among global and local features.

실시간으로 입력되는 영상으로부터 이동객체의 움직임 특징을 이용하여 움직임 분석에 적합한 디스크립터를 제안한다. 배경과 이동객체를 분리하기 위하여 배경학습을 행한다. 연속적으로 추출된 이동객체의 1차 모멘트를 이용하여 각 객체별로 이동 궤적을 추출한다. 연결 리스트를 이용하여 객체별로 추출된 1차 모멘트를 관리한다. 디스크립터는 격자 형태로 미리 지정된 9개의 지점 근방에 포함되는 이동객체의 1차 모멘트 좌표와 객체가 화면에 출현하는 시작 프레임 번호, 화면에서 사라지는 마지막 프레임 번호로 구성된다. 제안하는 전역 및 지역 특징 융합 디스크립터에 의한 비디오 검색은 둘 중 하나의 특징을 사용하는 기존의 방법에 비하여 효과적임을 확인하였다.

Keywords

References

  1. Young-jun Song, "Video Content Search Technology Trends," Korea Contents Association, Vol. 7, No. 1, pp. 46-52, 2009.
  2. N. Dimitrova and F. Golshani, "Motion recovery for video content classification," ACM Trans Information Systems, Vol. 13, No. 4, pp. 408-439, 1995. https://doi.org/10.1145/211430.211433
  3. Young-Eun An and Jong-An Park, "Color Correlogram using Combined RGB and HSV Color Spaces for Image Retrieval," Korea Instiute of Communications and Information Sciences, Vol 32 No.5 pp.513-519, 2007.
  4. Hyeok-June Jeon and Chi-Jung Hwang, "Image Matching (Correspondence Points) Based on Multi-resolution, Feature Point, Local Descriptor," Korean Society for Internet Information Conference, pp.5-848, 2010.
  5. Myoung-kwan Oh, Kun-hee Han, Dong-jin Choi and Byung-min Jun "Moving Object Tracking using Differential Image," Korea Contents Association Conference, Vol. 2, No. 1, pp. 396-400, 2004.
  6. Ja-Hwung Su, Yu-Ting Huang, Hsin-Ho Yeh and Vincent S. Tseng, "Effective content-based video retrieval using pattern-indexing and matching techniques," Expert System with Applications, Volume 37, Issue 7, pp. 5068-5085, 2010. https://doi.org/10.1016/j.eswa.2009.12.003
  7. Cl. Moranda, J. Benois-Pineaua, J. Ph. Domengera, J.Zepedab, E.Kijakc, and Ch. Guillemotb, "Scalable objectbased video retrieval in HD video databases," Signal Processing: Image Communication, Volume 25, Issue 6, pp.450-465, 2010. https://doi.org/10.1016/j.image.2010.04.004

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