Analysis of MPEG-4 Encoder for Object-based Video

실시간 객체기반 비디오 서비스를 위한 MPEG-4 Encoder 분석

  • Kim Min Hoon (Department of Information and Communication Engineering, Hanyang University) ;
  • Jang Euee Seon (Department of Information and Communication Engineering, Hanyang University) ;
  • Lee Sun young (Department of Information and Communication Engineering, Hanyang University) ;
  • Moon Seok ju (The College of Information and Communication Hanyang University)
  • 김민훈 (한양대학교 정보통신공학과) ;
  • 이선영 (한양대학교 정보통신공학과) ;
  • 문석주 (한양대학교 정보통신공학과) ;
  • 장의선 (한양대학교 정보통신학부)
  • Published : 2004.01.01

Abstract

In this paper, we have analyzed the current MPEG-4 video encoding tools and proposed efcient coding techniques that reduce the complexity of the encoder. Until recently, encoder optimization without shape coding has been a major concern in video for wire/wireless low bit rate coding services. Recently, we found out that the computational complexity of MPEG-4 shape coding plays a very important role in the object-based coding through experiments. We have made an experiment whether we could get optimized object-based coding method through successfully combining latest optimized texture coding techniques with our proposed optimized shape coding techniques. In texture coding, we applied the MVFAST method for motion estimation. We chose not to use IVOPF(Intelligent VOP Formation) but to use TRB(Tightest Rectangular Boundary) for positioning VOP and, finally, to eliminate the spiral search of shape motion estimation to reduce the complexity in shape coding. As a result of experiment, our proposed scheme achieved improved time complexity over the existing reference software by $57.3\%$ and over the optimized method on which only shape coding was applied by $48.7\%$, respectively.

본 논문에서는 현재 MPEG-4 비디오의 인코더를 분석하고 인코더의 복잡함을 줄일 수 있는 효율적인 압축기술을 제안하였다. 지금까지의 객체기반 비디오에서는 유/무선 저 전송률 부호화환경에 맞추기 위하여 형상부호화(Shape coding)를 제외한 인코더 최적화가 주를 이루었다. 최근에 본 연구팀이 수행한 형상부호화의 복잡도를 줄이기 위한 실험을 통하여 객체기반 부호화에서 형상부호화가 차지하는 계산비중이 상대적으로 높다는 것을 밝혀냈다 본 논문에서는 최근까지의 영상부호화 분야와 형상부호화 분야의 최적화 기술이 성공적으로 결합되어 최적의 객체기반 부호화 기술을 유도할 수 있는지 실험하였다 먼저 영상부호화 부분에서는 기존의 MEMC(Motion Estimation Motion Compensation)에서 사용된 검색 방법인 나선형 검색 대신에 MVFAST(Motion Vector Field Adaptive Search Technique) 기술을 채택하였고, 형상부호화 부분에서는 복잡함을 줄이기 위해 기존의 MEMC에서 사용된 나선형 검색을 생략하고 IVOPF(Intelligent VOP Formation) 대신 TRB(Tightest Rectangular Boundary)을 채택하여 최적화에 적용해 보았다. 실험결과, 객체기반 부호화를 위한 제안된 최적화 방식이 기존의 reference software 보다 $57.3\%$ 향상되었음을 알 수 있었다. 아울러, 본 논문에서 제안된 기술은 형상부호화 부분에만 적용된 최적화 기술보다 $50.8\%$ 향상된 실험결과를 보여주었다.

Keywords

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