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프레임 복잡도를 고려한 적응적 비트율 정규화 방법

Frame Complexity-Based Adaptive Bit Rate Normalization

  • 박상현 (순천대학교 멀티미디어공학과)
  • 투고 : 2015.10.21
  • 심사 : 2015.12.24
  • 발행 : 2015.12.31

초록

저전력 CMOS 카메라 기술의 발전으로 농업용 모니터링, 자연환경 감시 등의 다양한 비디오 센서네트워크 응용들에 대한 연구가 활발히 진행되고 있다. 이러한 응용들에서 핵심 기술은 영상을 어떻게 압축하고 전송할 것인가에 대한 것이다. 일반 센서 데이터에 비해 영상 데이터는 양이 크기 때문에 특히 트래픽에 대한 정확한 예측이 이루어져야만 광범위한 네트워크 자원을 효과적으로 관리할 수 있다. 본 논문에서는 비디오 센서 네트워크 환경에서 비디오 트래픽을 정확하게 예측하는 방법을 제안한다. 제안하는 방법은 영상의 복잡도를 측정하고 이 값을 적응적으로 트래픽 예측에 적용함으로써 기존의 방법들 보다 정확하게 압축 영상의 트래픽 양을 예측할 수 있다. 실험결과는 적응적 복잡도 예측을 이용한 제안하는 방법이 기존 방법에 비해 12% 이상 정확하게 결과 비트량을 예측하는 것을 보여준다.

Due to the advances in hardware technologies for low-power CMOS cameras, there have been various researches on wireless video sensor network(WVSN) applications including agricultural monitoring and environmental tracking. In such a system, its core technologies include video compression and wireless transmission. Since data of video sensors are bigger than those of other sensors, it is particularly necessary to estimate precisely the traffic after video encoding. In this paper, we present an estimation method for the encoded video traffic in WVSN networks. To estimate traffic characteristics accurately, the proposed method first measures complexities of frames and then applies them to the bit rate estimation adaptively. It is shown by experimental results that the proposed method improves the estimation of bit rate characteristics by more than 12% as compared to the existing method.

키워드

참고문헌

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