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Chung-Hua Yeh

dblp:13/8844 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2014
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Image and video coding · 75% Multimedia systems and quality of experience · 25%
Theoretical computer science
1 paper
Algorithms and data structures · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Image and video coding › error resilience
error concealment
0.212014
Motion Vector Recovery for Video Error Concealment by Using Iterative Dynamic-Programming Optimization · IEEE Trans. Multim. 2014
Image and video coding
error resilience
0.212014
Motion Vector Recovery for Video Error Concealment by Using Iterative Dynamic-Programming Optimization · IEEE Trans. Multim. 2014
Image and video coding › error resilience › error concealment
motion vector recovery
0.212014
Motion Vector Recovery for Video Error Concealment by Using Iterative Dynamic-Programming Optimization · IEEE Trans. Multim. 2014
Multimedia systems and quality of experience
video transmission
0.212014
Motion Vector Recovery for Video Error Concealment by Using Iterative Dynamic-Programming Optimization · IEEE Trans. Multim. 2014
Algorithms and data structures
dynamic programming
0.112014
Motion Vector Recovery for Video Error Concealment by Using Iterative Dynamic-Programming Optimization · IEEE Trans. Multim. 2014

Methods — techniques the papers use, named apart from their topics

iterative dynamic programming · 0.4boundary matching · 0.4
YearPublicationVenuePosition
2014 Motion Vector Recovery for Video Error Concealment by Using Iterative Dynamic-Programming Optimization
abstract
This paper proposes an error concealment technique for video transmission, focusing on motion vector (MV) recovery for both inter- and intra-coded frames, to improve video quality at decoder when video bit stream data incur transmission errors. The proposed algorithm considers slice (i.e., a row of macroblocks (MBs)) errors and uses DP (Dynamic Programming) optimization technique to estimate the lost MVs in a global manner, differing from the traditional Boundary Matching Algorithm (BMA) and others that recover MVs independently for individual MBs in an erroneous slice. We also propose an iterative DP process based on 8 × 8 pixels blocks to resolve finer motions (for 8 × 8, 8 × 16, and 16 × 8 pixels blocks) that will aid in the enhancement of reconstruction quality. Experiment results show that our algorithm outperforms the well-known BMA by up to 7.28 dB and the DMVE and another prior work by Qian by up to 1.0 dB at a packet loss rate of 15%. Subjective evaluation shows that our algorithm is especially promising in preserving line/curve features and motion details.
Wen-Nung Lie, Chang-Ming Lee, Chung-Hua Yeh, Zhi-Wei Gao 0001
IEEE Trans. Multim.3
2010 Video error concealment by using iterative dynamic-programming optimization
abstract
This paper addresses an error concealment technique, focusing on motion vector (MV) recovery for inter-coded frames, to improve video quality at decoder when video bit stream data are incurred transmission errors. The proposed algorithm considers slice (i.e., a row of macroblocks (MBs)) errors and uses DP (Dynamic Programming) optimization technique to estimate the lost MVs in a combined manner, differing from the traditional Boundary Matching Algorithm (BMA) which recovers MV independently for each erroneous MB. We also consider MV recovery for blocks of 8×8, 8×16, and 16×8 pixels (rather than 16×16 pixels MBs only) and apply an iterative DP process to refine the estimated results. Experimental results show that our algorithm outperforms the well-known BMA by up to 1.36 dB in PSNR and a newly published algorithm by up to 0.56 dB at a pack loss rate of up to 15%. Subjective evaluation shows that our algorithm takes the advantages of moderate speed and accurate recovery of contiguous line/curve features in images.
Wen-Nung Lie, Chung-Hua Yeh, Zhi-Wei Gao 0001
ICIP2