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A Cross-Diamond-Triangle Search Algorithm for Fast Block-Matching Motion Estimation (고속 블록 정합 움직임 측정을 위한 십자-다이아몬드-삼각 탐색 알고리즘)

  • Kim, Seong-Hoon;Shin, Jae-Min;Oh, Seoung-Jun;Ahn, Chang-Beom;Park, Ho-Chong;Sim, Dong-Gyu
    • Journal of Broadcast Engineering
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    • v.10 no.3
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    • pp.357-371
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    • 2005
  • In this Paper, we propose a new motion search algorithm called CDTS (Cross-Diamond-Triangle Search algorithm) that uses optimal search pattern according to the position of a search area to improve the performance of CDS(Cross-Diamond Search algorithm) as well as CDHSs(Cross-Diamond-Hexagonal Searches algorithms). We analyze motion distributions in various test video sequences to apply optimal search pattern according to a position of search area. Based on the result of this analysis, we propose a new triangle-shaped search pattern whose structure is asymmetric while previous search patterns are generally symmetric in conventional algorithms. In CDTS, we apply cross- and diamond-shaped search patterns to central search areas, and triangle- and diamond-shaped patterns to the other areas. Applying CDTS to test video sequences, the proposed scheme can reduce search points more than CDS and CDHSs by 16.22$\%$ and 3.09$\%$, respectively, without any visual quality degradation.

The Bi-Cross Pretraining Method to Enhance Language Representation (Bi-Cross 사전 학습을 통한 자연어 이해 성능 향상)

  • Kim, Sung-ju;Kim, Seonhoon;Park, Jinseong;Yoo, Kang Min;Kang, Inho
    • Annual Conference on Human and Language Technology
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    • 2021.10a
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    • pp.320-325
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    • 2021
  • BERT는 사전 학습 단계에서 다음 문장 예측 문제와 마스킹된 단어에 대한 예측 문제를 학습하여 여러 자연어 다운스트림 태스크에서 높은 성능을 보였다. 본 연구에서는 BERT의 사전 학습 문제 중 다음 문장 예측 문제에 대해 주목했다. 다음 문장 예측 문제는 자연어 추론 문제와 질의 응답 문제와 같이 임의의 두 문장 사이의 관계를 모델링하는 문제들에 성능 향상을 위해 사용되었다. 하지만 BERT의 다음 문장 예측 문제는 두 문장을 특수 토큰으로 분리하여 단일 문자열 형태로 모델에 입력으로 주어지는 cross-encoding 방식만을 학습하기 때문에 문장을 각각 인코딩하는 bi-encoding 방식의 다운스트림 태스크를 고려하지 않은 점에서 아쉬움이 있다. 본 논문에서는 기존 BERT의 다음 문장 예측 문제를 확장하여 bi-encoding 방식의 다음 문장 예측 문제를 추가적으로 사전 학습하여 단일 문장 분류 문제와 문장 임베딩을 활용하는 문제에서 성능을 향상 시키는 Bi-Cross 사전 학습 기법을 소개한다. Bi-Cross 학습 기법은 영화 리뷰 감성 분류 데이터 셋인 NSMC 데이터 셋에 대해 학습 데이터의 0.1%만 사용하는 학습 환경에서 Bi-Cross 사전 학습 기법 적용 전 모델 대비 5점 가량의 성능 향상이 있었다. 또한 KorSTS의 bi-encoding 방식의 문장 임베딩 성능 평가에서 Bi-Cross 사전 학습 기법 적용 전 모델 대비 1.5점의 성능 향상을 보였다.

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Modified Cross Search Algorithm for Fast Block Matching Motion Estimation (고속 블록 정합 움직임 추정을 위한 개선된 교차 탐색 알고리즘)

  • Ko, Byung-Kwan;Kwak, Tong-Ill;Hwang, Bo-Hyun;Yun, Jong-Ho;Choi, Myung-Ryul
    • Proceedings of the IEEK Conference
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    • 2008.06a
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    • pp.811-812
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    • 2008
  • In this paper, a modified cross search algorithm for fast block matching motion estimation is proposed. Various Motion Estimation (ME) algorithms have been proposed since ME requires large computational complexity. The proposed algorithm employs Modified Cross Search Pattern (MCSP) to search the motion vector. Efficient compression can be achieved since Modified Cross Search Algorithm (MCSA) simplifies the search pattern to reduce the computational complexity. The experimental results show that proposed algorithm reduces the search points up to 29% compared to conventional methods.

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A Fast Block Matching Algorithm by using the Cross Pattern and Flat-Hexagonal Search Pattern (크로스 패턴과 납작한 육각 탐색패턴을 이용한 고속 블록 정합 알고리즘)

  • 남현우;김종경
    • Journal of the Korea Computer Industry Society
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    • v.4 no.12
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    • pp.953-964
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    • 2003
  • In the block matching algorithm, search patterns of different shapes or sizes and the distribution of motion vectors have a large impact on both the searching speed and the image quality. In this paper, we propose a new fast block matching algorithm using the cross pattern and the flat-hexagon search pattern. Our algorithm first finds the motion vectors that are close to the center of search window using the cross pattern, and then lastly finds the other motion vectors that are not close to the center of search window using the flat-hexagon search pattern. Through experiments, compared with the hexagon-based search algorithm(HEXBS), the proposed cross pattern and flat-hexagonal pattern search algorithm(CFHPS ) improves about 0.2-6.2% in terms of average number of search point per motion vector estimation and improves about 0.02-0.31dB in terms of PSNR(Peak Signal to Noise Ratio).

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A New Cross and Hexagonal Search Algorithm for Fast Block Matching Motion Estimation (십자와 육각패턴을 이용한 고속 블록 정합 동작 예측 기법)

  • Park, In-Young;Nam, Hyeon-Woo;Wee, Young-Cheul;Kim, Ha-Jine
    • The KIPS Transactions:PartB
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    • v.10B no.7
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    • pp.811-814
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    • 2003
  • In this paper, we propose a fast block-matching motion estimation method using the cross pattern and the hexagonal pattern. For the block-matching motion estimation method, full search finds the best motion estimation, but it requires huge search time because it has to check every search point within the search window. The proposed method makes use of the fact that most of motion vectors lie near the center of block. The proposed method first uses the cross pattern to search near the center of block, and then uses the hexagonal pattern to search larger motion vectors. Experimental results show that our method is better than recently proposed search algorithms in terms of mean-square error performance and required search time.

CORRELATION SEARCH METHOD WITH THIRD-ORDER STATISTICS FOR COMPUTING VELOCITIES FROM MEDICAL IMAGES

  • Kim, D.;Lee, J.H.;Oh, M.H.
    • Proceedings of the KOSOMBE Conference
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    • v.1991 no.05
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    • pp.9-12
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    • 1991
  • The correlation search method yields velocity information by tracking scatter patterns between medical image frames. The displacement vector between a target region and the best correlated search region indicates the magnitude and direction of the inter-frame motion of that particular region. However, if the noise sources in the target region and the search region are correlated Gaussian, then the cross-correlation technique fails to work well because it estimates the cross-correlation of both signals and noises. In this paper we develop a new correlation search method which seeks the best correlated third-order statistics between a target and the search region to suppress the effect of correlated Gaussian noise sources. Our new method yields better estimations of velocity than the conventional cross-correlation method.

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Cross Diamond Search Using Motion Direction Biased Characteristics (움직임 방향 치우침 특성을 이용한 십자형 다이아몬드 탐색)

  • Ryu, Kwon-Yeol
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.13 no.8
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    • pp.1527-1533
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    • 2009
  • In this paper, we design directional search pattern using motion direction biased characteristics of MVP distribution, and proposes a direction applied cross diamond search method that adaptively change search pattern according to moving direction of search point. Proposed method predict motion vectors from neighbor macro blocks, and define initial motion direction by using predicted motion vectors. It improve search efficiency by using alternately proposed search pattern according to motion direction of BMP in search process. The simulation results show that proposed method is able to fast motion estimation compared with conventional cross diamond search, according as it reduce computational complexity that is required of motion estimation with $0.43%{\sim}1.76%$.

Cross-channel consumption behavior of clothing product - A cross-category analysis - (의류제품 크로스채널 소비행동 - 타제품군과의 비교 -)

  • Hong, Woo Jung;Lee, Kyu-Hye
    • The Research Journal of the Costume Culture
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    • v.27 no.2
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    • pp.98-108
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    • 2019
  • With the expansion of various distribution channels in online and offline stores, TV, and mobile, consumers now have more information search and retail selection channels to choose from than ever before. Major retailers now use multi- and omni-channel strategies. This study focused on cross-channel consumption, which involves the use of different information search and purchase channels. Using cross-channel consumption, consumers can search for information online and then make purchases offline and vice versa. The purpose of this study was to examine the relationship between channel strategies and other consumer variables, and the study also assessed the effect of product type. To conduct this empirical study, the researchers developed a consumer questionnaire concerning three consumer channel strategies-on-on, cross, and off-off-and four product categories-clothing, cosmetics, books, and electronics. The results indicated that gender and marital status did not influence consumer channel strategies, but that age did have a significant influence. The analysis showed that consumers in their 40s preferred the cross channel strategy, perceiving it to be effective, satisfactory, and rewarding. Compared to other products, clothing products showed higher levels of cross channel strategies. Consumers indicated that they prefer searching for information online and then purchasing clothing offline. Overall, clothing products generated higher levels of channel satisfaction and channel switch intentions. Cross-channel clothing shoppers reported effective information retrieval times but longer delivery times.

Enhanced Cross Search algorithm using Predicted Motion Vector for Fast Block Motion Estimation

  • Ko, Byung-Kwan;Kwak, Tong-Ill;Hwang, Bo-Hyun;Yun, Jong-Ho;Choi, Myung-Ryul
    • 한국정보디스플레이학회:학술대회논문집
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    • 2008.10a
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    • pp.749-752
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    • 2008
  • Various Motion Estimation (ME) algorithms have been proposed since ME requires large computational complexity. The proposed algorithm employs Enhanced Cross Search Pattern (ECSP) using motion vector of neighbor-blocks to search the motion vector. The experimental results show that proposed algorithm reduces the search point up to 35% compared to conventional methods.

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A Center Biased Cross-Diamond Search Algorithm for Fast Fractional-pel Motion Estimation (고속 부화소 움직임 추정을 위한 중심 지향적 십자 다이아몬드 탐색 알고리즘)

  • Jo, Seong-Hyeon;Lee, Jong-Hwa
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.46 no.2
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    • pp.78-84
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    • 2009
  • In general video coding systems, motion estimation (ME) is regarded as a vital component in a video coder as it consumes a large amount of computation resources. Fractional pixel motion estimation can improve the video compression rate at the cost of higher computational complexity. It is based on the experimental results that the sum of absolute differences (SAD) shows parabolic shape and thus can be approximated by using interpolation technique. In this paper, we propose a fast fractional pixel search algorithm by combining SASR (Simplified Adaptive Search Range) and the CBCDS (Center Biased Cross-Diamond Search) pattern with the predicted motion vector. Compare with the fractional pel full search and the CBFPS, the proposed CBCDS algorithms can reduce fractional pel search points up to 81.4%, respectively with the PSNR lost about 0.05dB.