• Title/Summary/Keyword: Speed Tracking

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Unified Detection and Tracking of Humans Using Gaussian Particle Swarm Optimization (가우시안 입자 군집 최적화를 이용한 사람의 통합된 검출 및 추적)

  • An, Sung-Tae;Kim, Jeong-Jung;Lee, Ju-Jang
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.4
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    • pp.353-358
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    • 2012
  • Human detection is a challenging task in many fields because it is difficult to detect humans due to their variable appearance and posture. Furthermore, it is also hard to track the detected human because of their dynamic and unpredictable behavior. The evaluation speed of method is also important as well as its accuracy. In this paper, we propose unified detection and tracking method for humans using Gaussian-PSO (Gaussian Particle Swarm Optimization) with the HOG (Histograms of Oriented Gradients) features to achieve a fast and accurate performance. Keeping the robustness of HOG features on human detection, we raise the process speed in detection and tracking so that it can be used for real-time applications. These advantages are given by a simple process which needs just one linear-SVM classifier with HOG features and Gaussian-PSO procedure for the both of detection and tracking.

MPPT Control of Photovoltaic System using HBPI Controller (HBPI 제어기를 이용한 태양광발전 시스템의 MPPT 제어)

  • Ko, Jae Sub;Chung, Dong-Hwa
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.61 no.12
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    • pp.1864-1871
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    • 2012
  • This paper proposes the hybrid proportional integral(HBPI) controller for maximum power point tracking(MPPT) control of photovoltaic system. The output characteristics of the solar cell are a nonlinear and affected by a temperature, the solar radiation and influence of a shadow. The MPPT control is a very important technique in order to increase an output and efficiency of the photovoltaic system. The conventional constant voltage(CV), perturbation and observation(PO) and incremental conductance(IC) are the method which finding maximum power point(MPP) by the continued self-excitation vibration, and uses the fixed step size. If the fixed step size is a large, the tracking speed of maximum power point is faster, but the tracking accuracy in the steady state is decreased. On the contrary, when the fixed step size is a small, the tracking accuracy is increased and the tracking speed is slower. Therefore, in order to solve these problems, this paper proposes HBPI controller that is adjusted gain of conventional PI control using fuzzy control, and the maximum power point tracks using this controller. The validity of the controller proposed in this paper proves through the results of the comparisons.

A Method of Lane Marker Detection Robust to Environmental Variation Using Lane Tracking (차선 추적을 이용한 환경변화에 강인한 차선 검출 방법)

  • Lee, Jihye;Yi, Kang
    • Journal of Korea Multimedia Society
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    • v.21 no.12
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    • pp.1396-1406
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    • 2018
  • Lane detection is a key function in developing autonomous vehicle technology. In this paper, we propose a lane marker detection algorithm robust to environmental variation targeting low cost embedded computing devices. The proposed algorithm consists of two phases: initialization phase which is slow but has relatively higher accuracy; and the tracking phase which is fast and has the reliable performance in a limited condition. The initialization phase detects lane markers using a set of filters utilizing the various features of lane markers. The tracking phase uses Kalman filter to accelerate the lane marker detection processing. In a tracking phase, we measure the reliability of the detection results and switch it to initialization phase if the confidence level becomes below a threshold. By combining the initialization and tracking phases we achieved high accuracy and acceptable computing speed even under a low cost computing resources in which we cannot use the computing intensive algorithm such as deep learning approach. Experimental results show that the detection accuracy is about 95% on average and the processing speed is about 20 frames per second with Raspberry Pi 3 which is low cost device.

Depth tracking of occluded ships based on SIFT feature matching

  • Yadong Liu;Yuesheng Liu;Ziyang Zhong;Yang Chen;Jinfeng Xia;Yunjie Chen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.4
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    • pp.1066-1079
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    • 2023
  • Multi-target tracking based on the detector is a very hot and important research topic in target tracking. It mainly includes two closely related processes, namely target detection and target tracking. Where target detection is responsible for detecting the exact position of the target, while target tracking monitors the temporal and spatial changes of the target. With the improvement of the detector, the tracking performance has reached a new level. The problem that always exists in the research of target tracking is the problem that occurs again after the target is occluded during tracking. Based on this question, this paper proposes a DeepSORT model based on SIFT features to improve ship tracking. Unlike previous feature extraction networks, SIFT algorithm does not require the characteristics of pre-training learning objectives and can be used in ship tracking quickly. At the same time, we improve and test the matching method of our model to find a balance between tracking accuracy and tracking speed. Experiments show that the model can get more ideal results.

Robust PID Controller Design for Speed Control of BLDC Motors (BLDC 모터 속도제어를 위한 견실 PID 제어기 설계)

  • 양승윤;김인수;전완수
    • Journal of the Korea Institute of Military Science and Technology
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    • v.5 no.1
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    • pp.75-82
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    • 2002
  • In this paper, the robust PID(Proportional-Integral-Derivative) controller was designed for speed control of BLDC motors using the frequency region model matching method. It was designed the robust PID controller satisfying disturbance attenuation and robust tracking performance using an H$\infty$ control method. The robust PID controller gains with the performances of the designed H$\infty$ controller are determined using the model matching method at frequency domain. Consequently, simulation results show that the proposed PID speed controller satisfies load torque disturbance attenuation and robust tracking performance, and this study has usefulness and applicability for the speed control system design of BLDC motors.

Implementation of Pedestrian Detection and Tracking with GPU at Night-time (GPU를 이용한 야간 보행자 검출과 추적 시스템 구현)

  • Choi, Beom-Joon;Yoon, Byung-Woo;Song, Jong-Kwan;Park, Jangsik
    • Journal of Broadcast Engineering
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    • v.20 no.3
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    • pp.421-429
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    • 2015
  • This paper is about an approach for pedestrian detection and tracking with infrared imagery. We used the CUDA(Computer Unified Device Architecture) that is a parallel processing language in order to improve the speed of video-based pedestrian detection and tracking. The detection phase is performed by Adaboost algorithm based on Haar-like features. Adaboost classifier is trained with datasets generated from infrared images. After detecting the pedestrian with the Adaboost classifier, we proposed a particle filter tracking strategies on HSV histogram feature that exploit adaptively at the same time. The proposed approach is implemented on an NVIDIA Jetson TK1 developer board that is full-featured device ideal for software development within the Linux environment. In this paper, we presented the results of parallel processing with the NVIDIA GPU on the CUDA development environment for detection and tracking of pedestrians. We compared the object detection and tracking processing time for night-time images on both GPU and CPU. The result showed that the detection and tracking speed of the pedestrian with GPU is approximately 6 times faster than that for CPU.

A Fast Semiautomatic Video Object Tracking Algorithm (고속의 세미오토매틱 비디오객체 추적 알고리즘)

  • Lee, Jong-Won;Kim, Jin-Sang;Cho, Won-Kyung
    • Proceedings of the KIEE Conference
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    • 2004.11c
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    • pp.291-294
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    • 2004
  • Semantic video object extraction is important for tracking meaningful objects in video and object-based video coding. We propose a fast semiautomatic video object extraction algorithm which combines a watershed segmentation schemes and chamfer distance transform. Initial object boundaries in the first frame are defined by a human before the tracking, and fast video object tracking can be achieved by tracking only motion-detected regions in a video frame. Experimental results shows that the boundaries of tracking video object arc close to real video object boundaries and the proposed algorithm is promising in terms of speed.

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Model-based sliding mode tracking control of 6-6 Stewart platform manipulator

  • Lee, Chong-Won;Kim, Nag-In
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.772-775
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    • 1997
  • A high speed tracking control for 6-6 Stewart platform manipulator is performed by employing the joint-axis sliding mode control based on dynamics. Because of the complex dynamics and kinematics of Stewart platform manipulator, two computer systems, consisting of a PC and a DSP, are adopted, so that real time tasks are run in synchronous and asynchronous modes. It is experimentally proven that the proposed control system leads to an easy to implement and effective control task, and it can achieve the high performance tracking control under the high speed and severe payload condition.

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Study for Improvement of Tracking Accuracy of the Feeding System with Iron Core Type Linear DC Motor by Neural Network Control (신경망 제어에 의한 철심형 리니어모터의 추종성 향상 연구)

  • 송창규;김경호;정재한
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2002.05a
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    • pp.73-77
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    • 2002
  • The requirements for higher productivity call for high speed of the machine tool axes. Iron core type linear DC motor is growly accepted far a viable candidate of the high speed machine tool feed unit. LDM, however, has inherent disturbance force components: cogging and force ripple. These disturbance force directly affects tracking accuracy of the carrage and must be eliminated or reduced. Reducing motor ripple, this paper adapted the feed forward compensation method and neural network control. Experiments carried 7ut on the linear motor test setup show that this control methods is usable in order to reduce the motor ripple.

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Red Light Running Enforcement System Using Real Time Individual Vehicle Tracking

  • Lim, Dae-Woon;Jun, Joon-Suk;Park, Sung-Hoon
    • 제어로봇시스템학회:학술대회논문집
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    • 2002.10a
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    • pp.115.5-115
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    • 2002
  • In this paper, we introduce a system that detects all kinds of violations at a street intersection such as red light running, speed violation, stop line violation and lane violation by tracking individual vehicles. Two cameras are used for defecting violations. One is an analog camera for real-time tracking and the other is a digital camera for license plate reading. This system is connected to the traffic signal system controller and monitors the red, arrow, yellow and green phases of an approach. Two loops in the road are used to detect vehicle approach and speed. The system takes pictures of all vehicles passing a second loop and tracks the vehicles until they go out a street intersection...

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