• Title/Summary/Keyword: Trajectory Classification

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Classification Type of Weapon Using Artificial Intelligence for Counter-battery RadarPaper Title (인공지능을 이용한 대포병탐지레이더의 탄종 식별)

  • Park, Sung-Jin;Jin, Hyung-Seuk
    • Journal of IKEEE
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    • v.24 no.4
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    • pp.921-930
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    • 2020
  • The Counter-battery radar estimates the origin and impact point of the artillery by tracking the trajectory of the shell. In addition, it has the ability of identifying the type of weapon. Depending on the position between the shell and the radar, the detected signals appear differently. This has ambiguity to distinguish the type of shells. This paper compares fuzzy logic and artificial intelligence, which classifies type of shell using the parameter of signal processing step. According to the research result, artificial intelligence can improve identification rate of type of shell. The data used in the experiment was obtained from a live fire detection test.

West seacoast wetland monitoring using KOMPSAT series imageries in high spatial resolution (고해상도 KOMPSAT 시리즈 이미지를 활용한 서해연안 습지 변화 모니터링)

  • Sunwoo, Wooyeon;Kim, Daeun;Kim, Seongkyun;Choi, Minha
    • Journal of Korea Water Resources Association
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    • v.50 no.6
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    • pp.429-440
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    • 2017
  • A series of multispectral high-resolution Korean Multi-Purpose Satellite (KOMPSAT) images were analyzed to detect the geographical changes in four different tidal flats in the west coast of South Korea. The method of unsupervised classification was used to generate a series of land use/land cover (LULC) maps from the satellite images, which were used as the input of the temporal trajectory analysis to detect the temporal change of coastal wetlands and its association with natural and anthropogenic activities. The accurately classified LULC maps extracted from the KOMPSAT images indicate that these multispectral high-resolution satellite data is highly applicable to generate good quality thematic maps for extracting wetlands. The result of the trajectory analysis showed that, while the tidal flat area of Gyeonggi and Jeollabuk provinces was estimated to have changed due to tidal effects, the reductive trajectory of the wetland areas belonging to the Saemangeum province was caused by a high degree of human-induced activities including large reclamation and urbanization. The conservation of the Jeungdo Wetland Protected Area in Jeollanam province revealed that the social and environmental policies can effectively protect coastal wetlands from degradation. Therefore, monitoring for wetland change using high resolution KOMPSAT is expected to be useful to coastal environment management and policy making.

Pedestrian Detection and Tracking Method for Autonomous Navigation Vehicle using Markov chain Monte Carlo Algorithm (MCMC 방법을 이용한 자율주행 차량의 보행자 탐지 및 추적방법)

  • Hwang, Jung-Won;Kim, Nam-Hoon;Yoon, Jeong-Yeon;Kim, Chang-Hwan
    • The Journal of Korea Robotics Society
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    • v.7 no.2
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    • pp.113-119
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    • 2012
  • In this paper we propose the method that detects moving objects in autonomous navigation vehicle using LRF sensor data. Object detection and tracking methods are widely used in research area like safe-driving, safe-navigation of the autonomous vehicle. The proposed method consists of three steps: data segmentation, mobility classification and object tracking. In order to make the raw LRF sensor data to be useful, Occupancy grid is generated and the raw data is segmented according to its appearance. For classifying whether the object is moving or static, trajectory patterns are analysed. As the last step, Markov chain Monte Carlo (MCMC) method is used for tracking the object. Experimental results indicate that the proposed method can accurately detect moving objects.

A Study on the Collision Avoidance of Two Manipulators using Velocity Modifications (속도 변형을 이용한 두 매니퓨레이터의 충돌회피에 대한 연구)

  • Bum-Hee Lee
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.37 no.8
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    • pp.563-569
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    • 1988
  • This research presents several velocity modification methods for collision avoidance of two manipulators in a common workspace. Due to the distinct nature of collision avoidance between the two manipulators, a new classification of collision situations is presented and utilized in planning a collision-free path. Concepts of a collision map and velocity modification are applied for realizing collision-free motion planning. An example is shown for velocity modification of a trajectory, which shows the significance of the proposed approaches in collision-free motion planneng of two moving robots.

A Fast Screening Algorithm for On-Line Transient Stability Assessment (온라인 과도안정도 판정을 위한 상정사고 고속 스크리닝 알고리즘 개발)

  • Yang, Jung-Dae;Lee, Jong-Seock;Lee, Byung-Jun;Kwon, Sae-Hyuk;Lee, Koung-Guk
    • Proceedings of the KIEE Conference
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    • 2000.11a
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    • pp.104-106
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    • 2000
  • Transient Stability of a power systems is its ability to maintain synchronous operation of machine when subjected to a large disturbance. This paper presents a new methodology for speed-up transient stability evaluation in SIME. SIME is a hybrid direct method including time simulation to enhance flexibility. The First features of the proposed method are that generator grouping can be performed even in very stable cases and that the stability of a contingency can be evaluated from a short period of time simulation results. The second features of the proposed method are that using power-angle trajectory and subdividing contingency classification have improved the screening capability.

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English Phoneme Recognition using Segmental-Feature HMM (분절 특징 HMM을 이용한 영어 음소 인식)

  • Yun, Young-Sun
    • Journal of KIISE:Software and Applications
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    • v.29 no.3
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    • pp.167-179
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    • 2002
  • In this paper, we propose a new acoustic model for characterizing segmental features and an algorithm based upon a general framework of hidden Markov models (HMMs) in order to compensate the weakness of HMM assumptions. The segmental features are represented as a trajectory of observed vector sequences by a polynomial regression function because the single frame feature cannot represent the temporal dynamics of speech signals effectively. To apply the segmental features to pattern classification, we adopted segmental HMM(SHMM) which is known as the effective method to represent the trend of speech signals. SHMM separates observation probability of the given state into extra- and intra-segmental variations that show the long-term and short-term variabilities, respectively. To consider the segmental characteristics in acoustic model, we present segmental-feature HMM(SFHMM) by modifying the SHMM. The SFHMM therefore represents the external- and internal-variation as the observation probability of the trajectory in a given state and trajectory estimation error for the given segment, respectively. We conducted several experiments on the TIMIT database to establish the effectiveness of the proposed method and the characteristics of the segmental features. From the experimental results, we conclude that the proposed method is valuable, if its number of parameters is greater than that of conventional HMM, in the flexible and informative feature representation and the performance improvement.

A Study on Hand-signal Recognition System in 3-dimensional Space (3차원 공간상의 수신호 인식 시스템에 대한 연구)

  • 장효영;김대진;김정배;변증남
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.41 no.3
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    • pp.103-114
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    • 2004
  • This paper deals with a system that is capable of recognizing hand-signals in 3-dimensional space. The system uses 2 color cameras as input devices. Vision-based gesture recognition system is known to be user-friendly because of its contact-free characteristic. But as with other applications using a camera as an input device, there are difficulties under complex background and varying illumination. In order to detect hand region robustly from a input image under various conditions without any special gloves or markers, the paper uses previous position information and adaptive hand color model. The paper defines a hand-signal as a combination of two basic elements such as 'hand pose' and 'hand trajectory'. As an extensive classification method for hand pose, the paper proposes 2-stage classification method by using 'small group concept'. Also, the paper suggests a complementary feature selection method from images from two color cameras. We verified our method with a hand-signal application to our driving simulator.

A Regional Trip Modes Classification Methodology Using Mobile Phone Data (모바일 데이터를 활용한 지역간 수단통행 분류 방법론 개발)

  • Kyuhyuk Kim;Hyorim Han;Dongho Kim;Tai jin Song
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.23 no.4
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    • pp.77-93
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    • 2024
  • The recent development of data collection technology, which conveys various travel data in real-world such as mobile data and probe vehicle data, facilitates transportation planners identifying specified spatio-temporal travel patterns. In this study, an easily implementable travel mode classification methodology was proposed to classify inter-regional trip-modes without modeling by superimposing trajectories generated from mobile phone signaling and transportation infrastructure points into a polygon scale of a shapefile in a GIS system. Each regional mode trip was classified according to the rules such as the presence of transportation infrastructure in the trip trajectory, travel time, and the presence of access trips. An accuracy test generates Type I and Type II error results table to verify the proposed methodology. As a result, it was found that the methodology developed showed the F1-Score of the air mode 1.00, rail mode 0.95, bus mode 0.73.

Development of deep learning base trajectory classification technology for multilog platform (다중로그 플랫폼을 위한 딥러닝 기반 경로 분류 기술 개발)

  • Shin, Won-Jae;Kwon, Eunjung;Park, Hyunho;Jung, Eui-Suk;Byon, Sungwon;Jang, Dong-Man;Lee, Yong-Tae
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2019.11a
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    • pp.71-72
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    • 2019
  • 최근 공공안전 분야에서는 국민의 위험상황을 분석하여 선제적으로 예측을 하여 국민의 안전을 보장하기 위한 요구사항이 대두대고 있다. 또한 스마트폰 및 스마트워치와 같은 고성능 모바일 단말 기기들의 대중화로 인해 해당 기기들에 부착된 다양한 센서 데이터들을 융복합하여 분석할 경우, 수집한 센서 데이터의 잠재적 가치를 안전보장 측면에서 사용할 수 있는 장점이 있다. 본 논문에서는 대인, 대물, 장소에 해당하는 로그 데이터들을 융복합 분석하여 보호대상자의 안전을 지원하는 다중로그 플랫폼 기반 이동경로 분석 기법을 제안한다. 다중로그 플랫폼에서 수집하는 보호대상자의 이동 경로 궤적을 활용하여 과거에 축적된 이동경로 패턴과 비교를 통해 현재 경로가 평소에 이용하던 경로와의 유사도를 추천하게 된다. 해당 이동 경로 분석 시스템은 위치기반 멀티모달 센서 데이터를 융복합 하여 보호대상자의 안전을 보장하는데 기여 할 것으로 예상된다.

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Baseball Game Analysis Method Using Broadcast Video (중계 영상을 활용한 야구 경기 분석 방법)

  • Son, Jong-Woong;Lee, Myeong-jin
    • Journal of Broadcast Engineering
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    • v.25 no.4
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    • pp.576-586
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    • 2020
  • Analyzing baseball games using sensors such as radars or riders is expensive. In this paper, we propose an algorithm to detect pitch shots and hit shots using baseball video and to generate ball trajectories within hit shots using camera movement. After the pitch shot and the hit shot detection using object detection and optical flow, we generate the transformation relationship between frames and ball locations in the frame, and calculates the ball trajectory. The performance of the proposed method is evaluated for three KBO baseball video sequences, and the detection accuracy and detection rate of pitch shot and hit shot were within 89-95 [%], and the average error for shot range was 13.6[m], The direction error was 7.5° and foul classification accuracy was 98.6%.