• Title/Summary/Keyword: Motion Information of Target

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Embedded SoC Design for H.264/AVC Decoder (H.264/AVC 디코더를 위한 Embedded SoC 설계)

  • Kim, Jin-Wook;Park, Tae-Geun
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.45 no.9
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    • pp.71-78
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    • 2008
  • In this paper, we implement the H.264/AVC baseline decoder by hardware-software partitioning under the embedded Linux Kernel 2.4.26 and the FPGA-based target board with ARM926EJ-S core. We design several IPs for the time-demanding blocks, such as motion compensation, deblocking filter, and YUV-to-RGB and they are communicated with the host through the AMBA bus protocol. We also try to minimize the number of memory accesses between IPs and the reference software (JM 11.0) which is ported in the embedded Linux. The proposed IPs and the system have been designed and verified in several stages. The proposed system decodes the QCIF sample video at 2 frame per second when 24MHz of system clock is running and we expect the bitter performance if the proposed system is designed with ASIC.

Study of Machine Learning based on EEG for the Control of Drone Flight (뇌파기반 드론제어를 위한 기계학습에 관한 연구)

  • Hong, Yejin;Cho, Seongmin;Cha, Dowan
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.249-251
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    • 2022
  • In this paper, we present machine learning to control drone flight using EEG signals. We defined takeoff, forward, backward, left movement and right movement as control targets and measured EEG signals from the frontal lobe for controlling using Fp1. Fp2 Fp2 two-channel dry electrode (NeuroNicle FX2) measuring at 250Hz sampling rate. And the collected data were filtered at 6~20Hz cutoff frequency. We measured the motion image of the action associated with each control target open for 5.19 seconds. Using Matlab's classification learner for the measured EEG signal, the triple layer neural network, logistic regression kernel, nonlinear polynomial Support Vector Machine(SVM) learning was performed, logistic regression kernel was confirmed as the highest accuracy for takeoff and forward, backward, left movement and right movement of the drone in learning by class True Positive Rate(TPR).

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Multi-axial Vibration Test on MAST System with Field Data (국내도로 주행 시험을 통한 6축 진동시험 방법에 관한 연구)

  • Kim, Chan-Jung;Bae, Chul-Yong;Lee, Bang-Hyun;Kwon, Seong-Jin;Na, Byung-Chul
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.16 no.7 s.112
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    • pp.704-711
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    • 2006
  • Vibration test on MAST(multi axial simulation table) system has several advantage over one-axial vibration test that could simulate 6-DOF, 3-axial translation and 3-axial moment, at the same time. Since field vibration motion can be fully represented with 6-DOF, multi-axial vibration test on vehicle component is widely conducted in technical leading companies to make sure its fatigue performance in vibration environment. On the way to fulfill the process, editing technique of obtained field data is key issue to success a reliable vibration testing with MAST system. Since the original signals are not only too large to fulfill it directly, but all of the measured data is not guarantee its convergency on generating its driving files, editing technique of the original signals are highly required to make some events that should meet the equal fatigue damage on the target component In this paper, key technique on editing a field data feasible for MAST system is described based on energy method in vibration fatigue. To explain its technique explicitly, author first introduced a process on field data acquisition of two vehicle component and then, representing events are produced to keep up with the editing strategy about a energy method. In the final chapter, a time information regarding a vibration test on MAST system is derived from the energy data which is critical information to perform a vibration test.

MAST Vibration on MAST System with Field Data (국내도로 주행 시험을 통한 6축 진동시험 방법에 관한 연구)

  • Kim, Chan-Jung;Bae, Chul-Yong;Lee, Bong-Hyun;Kwon, Seong-Jin;Na, Byung-Chul
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2006.05a
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    • pp.764-769
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    • 2006
  • Vibration test on MAST(multi axial simulation table) system has several advantage over one-axial vibration test that could simulate 6-DOF, 3-axial translation and 3-axial moment, at the same time. Since field vibration motion can be fully represented with 6-DOF, multi-axial vibration test on vehicle component is widely conducted in technical leading companies to make sure its fatigue performance in vibration environment. On the way to fulfill the process, editing technique of obtained field data is key issue to success a reliable vibration testing with MAST system. Since the original signals are not only too large to fulfill it directly, but all of the measured data is not guarantee its convergency on generating its driving files, editing technique of the original signals are highly required to make some events that should meet the equal fatigue damage on the target component In this paper, key technique on editing a field data feasible for MAST system is described based on energy method in vibration fatigue. To explain its technique explicitly, author first introduced a process on field data acquisition of two vehicle component and then, representing events are produced to keep up with the editing strategy about a energy method. In the final chapter, a time information regarding a vibration test on MAST system is derived from the energy data which is critical information to perform a vibration test.

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Data Augmentation using a Kernel Density Estimation for Motion Recognition Applications (움직임 인식응용을 위한 커널 밀도 추정 기반 학습용 데이터 증폭 기법)

  • Jung, Woosoon;Lee, Hyung Gyu
    • Journal of Korea Society of Industrial Information Systems
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    • v.27 no.4
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    • pp.19-27
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    • 2022
  • In general, the performance of ML(Machine Learning) application is determined by various factors such as the type of ML model, the size of model (number of parameters), hyperparameters setting during the training, and training data. In particular, the recognition accuracy of ML may be deteriorated or experienced overfitting problem if the amount of dada used for training is insufficient. Existing studies focusing on image recognition have widely used open datasets for training and evaluating the proposed ML models. However, for specific applications where the sensor used, the target of recognition, and the recognition situation are different, it is necessary to build the dataset manually. In this case, the performance of ML largely depends on the quantity and quality of the data. In this paper, training data used for motion recognition application is augmented using the kernel density estimation algorithm which is a type of non-parametric estimation method. We then compare and analyze the recognition accuracy of a ML application by varying the number of original data, kernel types and augmentation rate used for data augmentation. Finally experimental results show that the recognition accuracy is improved by up to 14.31% when using the narrow bandwidth Tophat kernel.

A Content-based Video Rate-control Algorithm Interfaced to Human-eye (인간과 결합한 내용기반 동영상 율제어)

  • 황재정;진경식;황치규
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.28 no.3C
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    • pp.307-314
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    • 2003
  • In the general multiple video object coder, more interested objects such as speaker or moving object is consistently coded with higher priority. Since the priority of each object may not be fixed in the whole sequence and be variable on frame basis, it must be adjusted in a frame. In this paper, we analyze the independent rate control algorithm and global algorithm that the QP value is controled by the static parameters, object importance or priority, target PSNR, weighted distortion. The priority among static parameters is analyzed and adjusted into dynamic parameters according to the visual interests or importance obtained by camera interface. Target PSNR and weighted distortion are proportionally derived by using magnitude, motion, and distortion. We apply those parameters for the weighted distortion control and the priority-based control resulting in the efficient bit-rate distribution. As results of this paper, we achieved that fewer bits are allocated for video objects which has less importance and more bits for those which has higher visual importance. The duration of stability in the visual quality is reduced to less than 15 frames of the coded sequence. In the aspect of PSNR, the proposed scheme shows higher quality of more than 2d13 against the conventional schemes. Thus the coding scheme interfaced to human- eye proves an efficient video coder dealing with the multiple number of video objects.

A Macroblock-Layer Rate Control for H.264/AVC Using Quadratic Rate-Distortion Model (2차원 비트율-왜곡 모델을 이용한 매크로블록 단위 비트율 제어)

  • Son, Nam-Rae;Lee, Guee-Sang;Yim, Chang-Hoon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.9C
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    • pp.849-860
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    • 2007
  • Because the H.264/AVC standard adopts the variable length coding algorithm, the rate of encoded video bitstream fluctuates a lot as time flows, though its compression efficiency is superior to that of existing standards. When a video is transmitted in real-time over networks with fixed low-bandwidth, it is necessary to control the bit rate which is generated from encoder. Many existing rate control algorithms have been adopting the quadratic rate-distortion model which determines the target bits for each frame. We propose a new rate control algorithm for H.264/AVC video transmission over networks with fixed bandwidth. The proposed algorithm predicts quantization parameter adaptively to reduce video distortion using the quadratic rate-distortion model, which uses the target bit rate and the mean absolute difference for current frame considering pixel difference between macroblocks in the previous and the current frame. On video samples with high motion and scene change cases, experimental results show that (1) the proposed algorithm adapts the encoded bitstream to limited channel capacity, while existing algorithms abruptly excess the limit bit rate; (2) the proposed algorithm improves picture quality with $0.4{\sim}0.9dB$ in average.

Numerical Study on the Development of the Seismic Response Prediction Method for the Low-rise Building Structures using the Limited Information (제한된 정보를 이용한 저층 건물 구조물의 지진 응답 예측 기법 개발을 위한 해석적 연구)

  • Choi, Se-Woon
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.33 no.4
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    • pp.271-277
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    • 2020
  • There are increasing cases of monitoring the structural response of structures using multiple sensors. However, owing to cost and management problems, limited sensors are installed in the structure. Thus, few structural responses are collected, which hinders analyzing the behavior of the structure. Therefore, a technique to predict responses at a location where sensors are not installed to a reliable level using limited sensors is necessary. In this study, a numerical study is conducted to predict the seismic response of low-rise buildings using limited information. It is assumed that the available response information is only the acceleration responses of the first and top floors. Using both information, the first natural frequency of the structure can be obtained. The acceleration information on the first floor is used as the ground motion information. To minimize the error on the acceleration history response of the top floor and the first natural frequency error of the target structure, the method for predicting the mass and stiffness information of a structure using the genetic algorithm is presented. However, the constraints are not considered. To determine the range of design variables that mean the search space, the parameter prediction method based on artificial neural networks is proposed. To verify the proposed method, a five-story structure is used as an example.

Efficient Object Selection Algorithm by Detection of Human Activity (행동 탐지 기반의 효율적인 객체 선택 알고리듬)

  • Park, Wang-Bae;Seo, Yung-Ho;Doo, Kyoung-Soo;Choi, Jong-Soo
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.47 no.3
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    • pp.61-69
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    • 2010
  • This paper presents an efficient object selection algorithm by analyzing and detecting of human activity. Generally, when people point any something, they will put a face on the target direction. Therefore, the direction of the face and fingers and was ordered to be connected to a straight line. At first, in order to detect the moving objects from the input frames, we extract the interesting objects in real time using background subtraction. And the judgment of movement is determined by Principal Component Analysis and a designated time period. When user is motionless, we estimate the user's indication by estimation in relation to vector from the head to the hand. Through experiments using the multiple views, we confirm that the proposed algorithm can estimate the movement and indication of user more efficiently.

Effect of strengthening and elongation exercises of upper extremity muscle to forward head posture correction

  • Lee, Jun Cheol
    • International journal of advanced smart convergence
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    • v.7 no.1
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    • pp.33-41
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    • 2018
  • This study was designed to provide basic data for developing exercise program that helps correcting posture by knowing the effect of strengthening and elongation exercises of upper extremity muscle to forward head posture correction. In this study determined subjects whether they had forward head posture or not. On the basis of the New York state posture rating, if a subject's posture is match up with the normal standard posture, gives 5 points and if the posture is slightly get out of the normal standard posture, gives 3 points and if the posture is apparently get out of the standard, gives 1 points. When determining the forward head posture, if talus, humerus and outer ear center are on the same line, it is determined as normal and if outer ear center is off the line less than 1.0cm, it is a slight deformation and if outer ear center is off the line more than 1.0cm, it is a high deformation. In the study selected people who have more than 1 cm gap between two vertical lines start from outer ear center and acromion separately as subjects. Length between the ideal alignment line measured by using goniometer and temporal region showed statistically significant decrease as $2.36{\pm}1.07cm$ before the intervention and $1.06{\pm}0.88cm$ after the intervention. After 4 weeks of neck and chest extensor muscle exercise, the group who exercised both showed increase in range of neck joint motion and neck flexion of the forward head posture. Meanwhile the group who only exercised neck extensor muscle only and the group who only exercised chest extensor muscle didn't showed statistically significant result. That only the group who exercised both muscles showed significant result is the different with studies before. Because this study didn't target patient who had a lesion, couldn't compare effect of the conservative manner and exercise. However, this study provides the fact that the group who exercised both neck and chest muscle had more effect than the control group.