1. Kalman Filter based Motion Vector Recovery for Interactive Video Gaming under Noisy Environments

Title(KR)

• 잡음환경에서의 비디오게임의 원활한 인터렉티브 비디오 스트림 제공을 위한 칼만필터 기반의 모션벡터 복구 기법

Title(ENG)

• Kalman Filter based Motion Vector Recovery for Interactive Video Gaming under Noisy Environments

Keywords(KR)

• H.264, Kalman Filter, SRMC (surrounding region matching criterion)

Keywords(ENG)

• H.264, Kalman Filter, SRMC (surrounding region matching criterion)

Author

• Seong-Whan Kim and Jae Youn Shim

Abstract(ENG)

As more computer game integrates with video and working under mobile environments, it requires seamless bandwidth limited video transport environment including integrated game video compression and real time video conference between game users. Video transmission system consists of encoder and decoder. In communication environment, when the encoder transmits the stream data to the decoder, the bit-stream is alternated or lost because of various channel noises. Altered and lost bit-stream data cause the loss of the video data intensity value or motion vector (MV) value. These lost data cause serious damage of the video quality. In this paper, we propose MV recovery method because MV is essential information to keep the better video quality. To recover the lost MV, we use adjacent block’s MV as input data of Kalman filter to estimate the optimized value for current block’s lost MV. In our experimentation with the standard video image: Mobile&Calendar and Susie, our proposed method achieved 0.497dB ~ 1.898dB improvements on video quality over no MV recovery and achieved average 0.03dB ~ 0.725dB improvements over SRMC scheme.

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