• Journal of Navigation and Port Research
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• v.48 no.2
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• pp.116-124
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• 2024

Automatic docking of small planing ship is a critical aspect of maritime operations, requiring accurate prediction of motion states to ensure safe and efficient maneuvers. This study investigates the use of Artificial Neural Network (ANN) to predict motion state of a small planing ship to enhance navigation automation in port environments. To achieve this, simulation tests were conducted to control a small planing ship while docking at various heading angles in calm water and in waves. Comprehensive analysis of the ANN-based predictive model was conducted by training and validation using data from various docking situations to improve its ability to accurately capture motion characteristics of a small planing ship. The trained ANN model was used to predict the motion state of the small planning ship based on any initial motion state. Results showed that the small planing ship could dock smoothly in both calm water and waves conditions, confirming the accuracy and reliability of the proposed method for prediction. Moreover, the ANN-based prediction model can adjust the dynamic model of the small planing ship to adapt in real-time and enhance the robustness of an automatic positioning system. This study contributes to the ongoing development of automated navigation systems and facilitates safer and more efficient maritime transport operations.

• Journal of Broadcast Engineering
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• v.17 no.6
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• pp.976-989
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• 2012

In this paper, we propose an efficient motion prediction architecture and DPB design mechanism for scalable multi-view video coding which is implemented by integrating SVC and MVC coding algorithms. In the proposed motion prediction architecture, we employ pictures associated with other views as a candidate for reference picture for improved motion prediction performance. By the proposed prediction architecture, we could enormously reduce the size of compressed video data. When performing scalable multi-view video coding, an integrated DPB design mechanism is also proposed. It is shown by various simulations that the proposed motion prediction architecture for scalable multi-view video coding can result in reduced data size in the compressed bitstream.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.10
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• pp.927-932
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• 2010

Estimation methods of motion intention from bio-signal present challenges in man machine interaction(MMI) to offer user's command to machine without control of any devices. Measurements of meaningful bio-signals that contain the motion intention and motion estimation methods from bio-signal are important issues for accurate and safe interaction. This paper proposes a novel motion estimation sensor based on a geometrical muscle changes, and a motion estimation method using the sensor. For estimation of the motion, we measure the circumference change of the muscle which is proportional to muscle activation level using a flexible piezoelectric cable (pMAS, piezo muscle activation sensor), designed in band type. The pMAS measures variations of the cable band that originate from circumference changes of muscle bundles. Moreover, we estimate the elbow motion by applying the sensor to upper limb with least square method. The proposed sensor and prediction method are simple to use so that they can be used to motion prediction device and methods in rehabilitation and sports fields.

• ETRI Journal
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• v.35 no.6
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• pp.990-1000
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• 2013

This paper describes the scalable extension of High Efficiency Video Coding (HEVC) to provide flexible high-quality digital video content services. The proposed scalable codec is designed on multi-loop decoding architecture to support inter-layer sample prediction and inter-layer motion parameter prediction. Inter-layer sample prediction is enabled by inserting the reconstructed picture of the reference layer (RL) into the decoded picture buffer of the enhancement layer (EL). To reduce the motion parameter redundancies between layers, the motion parameter of the RL is used as one of the candidates in merge mode and motion vector prediction in the EL. The proposed scalable extension can support scalabilities with minimum changes to the HEVC and provide average Bj${\o}$ntegaard delta bitrate gains of about 24% for spatial scalability and of about 21% for SNR scalability compared to simulcast coding with HEVC.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.5
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• pp.94-102
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• 1998

In this paper, we proposed a dynamic selection scheme of advnaced prediction mode(DAPM), which reduces computational cost and improves coding efficiency. We can select the mode between default prediction mode (DPM) and advanced prediction mode (APM) according to motion componenets in a frame dynamically. For this purpose, we defined error distribution of motion estimation (EDME) as sum of absolute difference(SAD) for each searching points. This distribution region is divided to four subregions. We calculate minimum values in each subregions and then, we determine whether block motion estimation is performed or not depending on the results. As a result, we reduced computational complexity to 30% without degradation of image quality compared to fixed APM(FAPM) by selecting DPM for linear movement.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.2
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• pp.37-48
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• 2008

Generally, a motion vector and a disparity vector represent the motion information of an object in a single-view of camera and the displacement of the same scene between two cameras that located spatially different from each other, respectively. Conventional H.264/AVC does not use the disparity vector in the motion vector prediction because H.264/AVC has been developed for the single-view video. But, multi-view video coding that uses the inter-view prediction structure based on H.264/AVC can make use of the disparity vector instead of the motion vector when the current frame refers to the frame of different view. Therefore, in this paper, we propose an improved motion/disparity vector prediction method that consists of global disparity vector replacement and extended neighboring block prediction. From the experimental results of the proposed method compared with the conventional motion vector prediction of H.264/AVC, we achieved average 1.07% and 1.32% of BD (Bjontegaard delta)-bitrate saving for ${\pm}32$ and ${\pm}64$ of global vector search range, respectively, when the search range of the motion vector prediction is set to ${\pm}16$.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.397-400
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• 2016

In this paper, we propose an efficient algorithm for computing architecture for high-performance Inter Prediction SAD HEVC encoder. HEVC Motion Estimation (ME) of the Inter Prediction is a process for searching for the currently high prediction block PU and the correlation in the interpolated reference picture in order to remove temporal redundancy. ME algorithm uses full search(FS) or fast search algorithm. Full search technique has the guaranteed optimal results but has many disadvantages which include high calculation and operational time due to the motion prediction with respect to all candidate blocks in a given search area. Therefore, this paper proposes a new algorithm which reduces the computational complexity by reusing the SAD operation in full search to reduce the amount of calculation and computational time of the Inter Prediction. The proposed algorithm is applied to an HEVC standard software HM16.12. There was an improved operational time of 61% compared to the traditional full search algorithm, BDBitrate was decreased by 11.81% and BDPSNR increased by about 0.5%.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.601-604
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• 1999

We propose a new hierarchical motion estimator architecture that supports the advanced prediction mode of recent low bit-rate video coders such as H.263 and MPEG-4. In the proposed VLSI architecture, a basic searching unit (BSU) is commonly utilized for all hierarchical levels to make a systematic and small sized motion estimator. Since the memory bank of the proposed architecture provides scheduled data flow for calculating 8$\times$8 block-based sum of absolute difference (SAD), both a macroblock-based motion vector (MV) and four block-based MVs are simultaneously obtained for each macroblock in the advanced prediction mode. The proposed motion estimator gives similar coding performance compared with full search block matching algorithm (FSBMA) while achieving small size and satisfying the advanced prediction mode.

• ETRI Journal
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• v.34 no.5
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• pp.753-758
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• 2012

As the next-generation video coding standard, High Efficiency Video Coding (HEVC) has adopted advanced coding tools despite the increase in computational complexity. In this paper, we propose a selective bi-prediction method to reduce the encoding complexity of HEVC. The proposed method evaluates the statistical property of the sum of absolute differences in the motion estimation process and determines whether bi-prediction is performed. A performance comparison of the complexity reduction is provided to show the effectiveness of the proposed method compared to the HEVC test model version 4.0. On average, 50% of the bi-prediction time can be reduced by the proposed method, while maintaining a negligible bit increment and a minimal loss of image quality.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.4
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• pp.736-739
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• 2009

In this paper, an efficient lossless compression algorithm using motion adaptation is proposed. It is divided into two parts: a motion adaptation based nonlinear predictor part and a residual data coding part. The proposed nonlinear predictor can reduce prediction error by learning from its past prediction errors using motion adaption. The predictor decides the proper selection of the intra and inter prediction values according to the past prediction error. The reduced error is coded by existing context adaptive coding method. Experimental results show that the proposed algorithm has the higher compression ratio than context modeling methods, such as FELICS, CALIC, and JPEG-LS.