Browsing by Author "Chin, Yi"

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BAYESIAN DENSE MOTION FIELD ESTIMATION WITH LANDMARK CONSTRAINT
(2010)
Chin, Yi
;
Tsai, Chun-Jen
;
資訊工程學系
;
Department of Computer Science
In this paper, a dense motion field estimation technique based on the Bayesian framework is proposed to estimate the true dense motion fields of video sequences. Previous stochastic techniques of dense motion field estimation adopts piecewise smooth motion model and use MAP estimation to find the motion field with joint minimization of motion compensation errors and maximization of motion smoothness. However, such random process does not guarantee to converge to the true motion field. In this paper, the motion of landmark points in the video sequence is introduced into the MAP estimation process to regularize the estimated motion field. Experimental results show that the proposed algorithm produces estimated motion fields which preserve piecewise smooth nature and are visually close to the true motion of the video sequences.
DENSE TRUE MOTION FIELD COMPENSATION FOR VIDEO CODING
(2013-01-01)
Chin, Yi
;
Tsai, Chun-Jen
;
資訊工程學系
;
Department of Computer Science
In this paper, a new motion compensation scheme based on dense true motion fields is investigated for video coding. The proposed technique is similar to the block-based decoder-side motion estimation method except that dense motion fields estimated from previously decoded frames are used for frame prediction. This paper demonstrates that even with compression distortions, an iterative dense true motion estimation technique can still produce good quality dense motion fields for video coding or frame-rate up-sampling applications. In particular, we have shown that when the new dense motion field compensation tool is integrated into the B-frame codec of H.264, one can achieve up to 8% overall BD bit-rate savings using standard MPEG test sequences.