• Title/Summary/Keyword: motion optimization

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An Efficient coding Method for Motion Prediction Flag in the Scalable Video Encoding Standard (스케일러블 동영상 부호화 표준에서 움직임 예측 플래그를 위한 효율적인 부호화 방식)

  • Moon, Yong-Ho;Eom, Il-Kyu;Ha, Seok-Wun
    • IEMEK Journal of Embedded Systems and Applications
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    • v.9 no.2
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    • pp.81-86
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    • 2014
  • In the scalable video coding standard, inter-layer prediction based on the coding information of the base layer was adopted to increase the coding performance. This prediction tool results in new syntax elements called motion_prediction_flag (mPF) and residul_prediction_flag(rPF), which are carried to notify the motion vector predictor (MVP) and reference block required in the motion compensation of the decoder. In this paper, an efficient coding method for mPF is proposed to enhance coding efficiency of the salable video coding standard. Through an analysis on the transmission of mPF based on the relationship between the MVPs, we discover the conditions where mPF is unnecessary at the decoder and suggest a modified rate-distortion (RD) cost function to make RD optimization more effective. Simulation results show that the proposed method offers BD rate savings of approximately 1.4%, compared with the conventional SVC standard.

Motion Estimation Using 3-D Straight Lines (3차원 직선을 이용한 카메라 모션 추정)

  • Lee, Jin Han;Zhang, Guoxuan;Suh, Il Hong
    • The Journal of Korea Robotics Society
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    • v.11 no.4
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    • pp.300-309
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    • 2016
  • This paper proposes a method for motion estimation of consecutive cameras using 3-D straight lines. The motion estimation algorithm uses two non-parallel 3-D line correspondences to quickly establish an initial guess for the relative pose of adjacent frames, which requires less correspondences than that of current approaches requiring three correspondences when using 3-D points or 3-D planes. The estimated motion is further refined by a nonlinear optimization technique with inlier correspondences for higher accuracy. Since there is no dominant line representation in 3-D space, we simulate two line representations, which can be thought as mainly adopted methods in the field, and verify one as the best choice from the simulation results. We also propose a simple but effective 3-D line fitting algorithm considering the fact that the variance arises in the projective directions thus can be reduced to 2-D fitting problem. We provide experimental results of the proposed motion estimation system comparing with state-of-the-art algorithms using an open benchmark dataset.

Spatial Multilevel Optical Flow Architecture-based Dynamic Motion Estimation in Vehicular Traffic Scenarios

  • Fuentes, Alvaro;Yoon, Sook;Park, Dong Sun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.12
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    • pp.5978-5999
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    • 2018
  • Pedestrian detection is a challenging area in the intelligent vehicles domain. During the last years, many works have been proposed to efficiently detect motion in images. However, the problem becomes more complex when it comes to detecting moving areas while the vehicle is also moving. This paper presents a variational optical flow-based method for motion estimation in vehicular traffic scenarios. We introduce a framework for detecting motion areas with small and large displacements by computing optical flow using a multilevel architecture. The flow field is estimated at the shortest level and then successively computed until the largest level. We include a filtering parameter and a warping process using bicubic interpolation to combine the intermediate flow fields computed at each level during optimization to gain better performance. Furthermore, we find that by including a penalization function, our system is able to effectively reduce the presence of outliers and deal with all expected circumstances in real scenes. Experimental results are performed on various image sequences from Daimler Pedestrian Dataset that includes urban traffic scenarios. Our evaluation demonstrates that despite the complexity of the evaluated scenes, the motion areas with both moving and static camera can be effectively identified.

A Data-driven Classifier for Motion Detection of Soldiers on the Battlefield using Recurrent Architectures and Hyperparameter Optimization (순환 아키텍쳐 및 하이퍼파라미터 최적화를 이용한 데이터 기반 군사 동작 판별 알고리즘)

  • Joonho Kim;Geonju Chae;Jaemin Park;Kyeong-Won Park
    • Journal of Intelligence and Information Systems
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    • v.29 no.1
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    • pp.107-119
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    • 2023
  • The technology that recognizes a soldier's motion and movement status has recently attracted large attention as a combination of wearable technology and artificial intelligence, which is expected to upend the paradigm of troop management. The accuracy of state determination should be maintained at a high-end level to make sure of the expected vital functions both in a training situation; an evaluation and solution provision for each individual's motion, and in a combat situation; overall enhancement in managing troops. However, when input data is given as a timer series or sequence, existing feedforward networks would show overt limitations in maximizing classification performance. Since human behavior data (3-axis accelerations and 3-axis angular velocities) handled for military motion recognition requires the process of analyzing its time-dependent characteristics, this study proposes a high-performance data-driven classifier which utilizes the long-short term memory to identify the order dependence of acquired data, learning to classify eight representative military operations (Sitting, Standing, Walking, Running, Ascending, Descending, Low Crawl, and High Crawl). Since the accuracy is highly dependent on a network's learning conditions and variables, manual adjustment may neither be cost-effective nor guarantee optimal results during learning. Therefore, in this study, we optimized hyperparameters using Bayesian optimization for maximized generalization performance. As a result, the final architecture could reduce the error rate by 62.56% compared to the existing network with a similar number of learnable parameters, with the final accuracy of 98.39% for various military operations.

Acceleration Optimization of a High-speed LCD Transfer Crane Using Finite Jerk (고속 LCD 이송 시스템의 진동감소를 위한 Finite Jerk 적용 가속도 최적화)

  • Chung W.J.;Song T.J.;Jung D.W.;Cho Y.D.;Bang D.J.;Yoon Y.M.
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2005.06a
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    • pp.1906-1909
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    • 2005
  • This paper presents the acceleration optimization of a high-speed LCD (Liquid Crystal Display) transfer system for the minimization of vibration. To reduce vibration is one of key requirements for the dynamic control of a high-speed LCD transfer system. In this paper, the concept of finite jerk (the first derivative of acceleration) has been introduced for realizing input acceleration. The profile of finite jerk has been optimized using a genetic algorithm so that vibration effect can be minimized. In order to incorporate a genetic algorithm, the dynamic model of a LCD transfer system which is realized by using the $ADAMS^{(R){$ software has been linked to the simulation system constructed by the $MATLAB^{(R)}$. The simulation results illustrated that the duration of finite jerk can be optimized so as to minimize the magnitude of vibration. It has been also shown that the acceleration optimization with finite jerk can make the high-speed motion of a LCD transfer system result in low vibration, compared with the conventional motion control with trapezoidal velocity profile.

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Deep Learning-Based Human Motion Denoising (딥 러닝 기반 휴먼 모션 디노이징)

  • Kim, Seong Uk;Im, Hyeonseung;Kim, Jongmin
    • Journal of IKEEE
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    • v.23 no.4
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    • pp.1295-1301
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    • 2019
  • In this paper, we propose a novel method of denoising human motion using a bidirectional recurrent neural network (BRNN) with an attention mechanism. The corrupted motion captured from a single 3D depth sensor camera is automatically fixed in the well-established smooth motion manifold. Incorporating an attention mechanism into BRNN achieves better optimization results and higher accuracy than other deep learning frameworks because a higher weight value is selectively given to a more important input pose at a specific frame for encoding the input motion. Experimental results show that our approach effectively handles various types of motion and noise, and we believe that our method can sufficiently be used in motion capture applications as a post-processing step after capturing human motion.

A multi-objective optimization framework for optimally designing steel moment frame structures under multiple seismic excitations

  • Ghasemof, Ali;Mirtaheri, Masoud;Mohammadi, Reza Karami;Salkhordeh, Mojtaba
    • Earthquakes and Structures
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    • v.23 no.1
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    • pp.35-57
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    • 2022
  • This article presents a computationally efficient framework for multi-objective seismic design optimization of steel moment-resisting frame (MRF) structures based on the nonlinear dynamic analysis procedure. This framework employs the uniform damage distribution philosophy to minimize the weight (initial cost) of the structure at different levels of damage. The preliminary framework was recently proposed by the authors based on the single excitation and the nonlinear static (pushover) analysis procedure, in which the effects of record-to-record variability as well as higher-order vibration modes were neglected. The present study investigates the reliability of the previous framework by extending the proposed algorithm using the nonlinear dynamic design procedure (optimization under multiple ground motions). Three benchmark structures, including 4-, 8-, and 12-story steel MRFs, representing the behavior of low-, mid-, and high-rise buildings, are utilized to evaluate the proposed framework. The total weight of the structure and the maximum inter-story drift ratio (IDRmax) resulting from the average response of the structure to a set of seven ground motion records are considered as two conflicting objectives for the optimization problem and are simultaneously minimized. The results of this study indicate that the optimization under several ground motions leads to almost similar outcomes in terms of optimization objectives to those are obtained from optimization under pushover analysis. However, investigation of optimal designs under a suite of 22 earthquake records reveals that the damage distribution in buildings designed by the nonlinear dynamic-based procedure is closer to the uniform distribution (desired target during the optimization process) compared to those designed according to the pushover procedure.

Optimal Design of the Optical Pickup Actuator Coil (광픽업 구동기 코일최적설계)

  • Yoon Young, Kim;Woochun, Kim;Jae Eun, Kim
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2004.05a
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    • pp.352-355
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    • 2004
  • The objective of this work is to develop a new design method to find optimal coils, especially the optimal coil configuration of an optical pickup actuator. In designing actuator coils, the developed Lorenz force in the coils along the desired direction should be made as large as possible while forces and torques in other directions should be made as small as possible. The design methodology we are developing is a systematic approach that can generate optimal coil configurations for given permanent magnet configurations. To consider the best coil configuration among all feasible coil configurations, we formulate the design problem as a topology optimization of a coil. The present formulation for coil design is noble in the sense that the existing topology optimization is mainly concerned with the design of yokes and permanent magnets and that the optimization of actuator coils is so far limited within shape or size optimization. Though the present design methodology applies to any problem, the specific design example considered is the design of fine-pattern tracking and focusing coils.

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Optimization of Railway Alignment Using GIS (GIS를 이용한 철도선형최적화)

  • 강인준;이준석;김수성
    • Proceedings of the KSR Conference
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    • 2002.10a
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    • pp.727-732
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    • 2002
  • This study is to develop the model of alignment optimization based on design criteria by approaching through alignment of railway design and problems in economy, environment and technology for satisfying traffic volume of the main roads caused by economical and social developments. Now, Geographic Information System isn't applied when designing a present railway in home. And the design of railway alignment is still set on importance of transition curves and cant according to passenger comfort in abroad so tile study of railway alignment is at initiation phase so far. This paper is about decision of optimal alignment between two stations such as starting point and ending point automatically using GIS in optimization of railway alignment. A route between Sungsan city and Shinpung city is the training area and the study compared and evaluated optimal railway route by GIS automatically with present railway route designed. Present optimal fomulas was used in this study for optimization of railway alignment. The model of optimization of railway alignment was developed through topographical elements and it was mentioned by the model of road alignment because of the similarity in design of alignment. But the design of lateral track irregularities, cant fur passenger comfort and motion sickness fellowed by train rolling have to be considered more. Anyway, this study farmed the basis of using GIS and the study should be keep going on in the future.

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Robust Design Optimization of the Vehicle Ride Comfort Considering Variation of the Design Parameters (설계변수의 산포를 고려한 차량 승차감의 강건최적설계)

  • Song, Pil-Gon;Spiriyagin, Maksym;Yoo, Hong-Hee
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.18 no.12
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    • pp.1217-1223
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    • 2008
  • Vehicle vibration mostly originates from the road excitation and causes discomfort, fatigue and even injury to a driver. Vehicle ride comfort is one of the most important performance indices to achieve a high-quality vehicle design. Since design parameter variations inevitably result in the vehicle ride comfort variance, the variance characteristics should be analyzed in the early design stage of the vehicle. The vehicle ride comfort is often defined by an index which employs a weighted RMS value of the acceleration PSD of a seat position. The design solution is obtained through two steps in this study. An optimization problem to obtain a minimum ride comfort index is solved first. Then another optimization problem to obtain minimum variance of the ride comfort index is solved. For the optimization problems, the equations of motion and the sensitivity equations are derived basing on a 5-DOF vehicle model. The numerical results show that an optimal solution for the minimum ride comfort is not necessarily same as that of the minimum variance of the ride comfort.