• Title/Summary/Keyword: multi-target tracking

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Implementation of Specific Target Detection and Tracking Technique using Re-identification Technology based on public Multi-CCTV (공공 다중CCTV 기반에서 재식별 기술을 활용한 특정대상 탐지 및 추적기법 구현)

  • Hwang, Joo-Sung;Nguyen, Thanh Hai;Kang, Soo-Kyung;Kim, Young-Kyu;Kim, Joo-Yong;Chung, Myoung-Sug;Lee, Jooyeoun
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.22 no.4
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    • pp.49-57
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    • 2022
  • The government is making great efforts to prevent crimes such as missing children by using public CCTVs. However, there is a shortage of operating manpower, weakening of concentration due to long-term concentration, and difficulty in tracking. In addition, applying real-time object search, re-identification, and tracking through a deep learning algorithm showed a phenomenon of increased parameters and insufficient memory for speed reduction due to complex network analysis. In this paper, we designed the network to improve speed and save memory through the application of Yolo v4, which can recognize real-time objects, and the application of Batch and TensorRT technology. In this thesis, based on the research on these advanced algorithms, OSNet re-ranking and K-reciprocal nearest neighbor for re-identification, Jaccard distance dissimilarity measurement algorithm for correlation, etc. are developed and used in the solution of CCTV national safety identification and tracking system. As a result, we propose a solution that can track objects by recognizing and re-identification objects in real-time within situation of a Korean public multi-CCTV environment through a set of algorithm combinations.

Performance Improvement of Pedestrian Detection using a GM-PHD Filter (GM-PHD 필터를 이용한 보행자 탐지 성능 향상 방법)

  • Lee, Yeon-Jun;Seo, Seung-Woo
    • Journal of the Institute of Electronics and Information Engineers
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    • v.52 no.12
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    • pp.150-157
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    • 2015
  • Pedestrian detection has largely been researched as one of the important technologies for autonomous driving vehicle and preventing accidents. There are two categories for pedestrian detection, camera-based and LIDAR-based. LIDAR-based methods have the advantage of the wide angle of view and insensitivity of illuminance change while camera-based methods have not. However, there are several problems with 3D LIDAR, such as insufficient resolution to detect distant pedestrians and decrease in detection rate in a complex situation due to segmentation error and occlusion. In this paper, two methods using GM-PHD filter are proposed to improve the poor rates of pedestrian detection algorithms based on 3D LIDAR. First one improves detection performance and resolution of object by automatic accumulation of points in previous frames onto current objects. Second one additionally enhances the detection results by applying the GM-PHD filter which is modified in order to handle the poor situation to classified multi target. A quantitative evaluation with autonomously acquired road environment data shows the proposed methods highly increase the performance of existing pedestrian detection algorithms.

Improving target recognition of active sonar multi-layer processor through deep learning of a small amounts of imbalanced data (소수 불균형 데이터의 심층학습을 통한 능동소나 다층처리기의 표적 인식성 개선)

  • Young-Woo Ryu;Jeong-Goo Kim
    • The Journal of the Acoustical Society of Korea
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    • v.43 no.2
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    • pp.225-233
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    • 2024
  • Active sonar transmits sound waves to detect covertly maneuvering underwater objects and detects the signals reflected back from the target. However, in addition to the target's echo, the active sonar's received signal is mixed with seafloor, sea surface reverberation, biological noise, and other noise, making target recognition difficult. Conventional techniques for detecting signals above a threshold not only cause false detections or miss targets depending on the set threshold, but also have the problem of having to set an appropriate threshold for various underwater environments. To overcome this, research has been conducted on automatic calculation of threshold values through techniques such as Constant False Alarm Rate (CFAR) and application of advanced tracking filters and association techniques, but there are limitations in environments where a significant number of detections occur. As deep learning technology has recently developed, efforts have been made to apply it in the field of underwater target detection, but it is very difficult to acquire active sonar data for discriminator learning, so not only is the data rare, but there are only a very small number of targets and a relatively large number of non-targets. There are difficulties due to the imbalance of data. In this paper, the image of the energy distribution of the detection signal is used, and a classifier is learned in a way that takes into account the imbalance of the data to distinguish between targets and non-targets and added to the existing technique. Through the proposed technique, target misclassification was minimized and non-targets were eliminated, making target recognition easier for active sonar operators. And the effectiveness of the proposed technique was verified through sea experiment data obtained in the East Sea.

Implementation of Virtual Instrumentation based Realtime Vision Guided Autopilot System and Onboard Flight Test using Rotory UAV (가상계측기반 실시간 영상유도 자동비행 시스템 구현 및 무인 로터기를 이용한 비행시험)

  • Lee, Byoung-Jin;Yun, Suk-Chang;Lee, Young-Jae;Sung, Sang-Kyung
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.9
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    • pp.878-886
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    • 2012
  • This paper investigates the implementation and flight test of realtime vision guided autopilot system based on virtual instrumentation platform. A graphical design process via virtual instrumentation platform is fully used for the image processing, communication between systems, vehicle dynamics control, and vision coupled guidance algorithms. A significatnt ojective of the algorithm is to achieve an environment robust autopilot despite wind and an irregular image acquisition condition. For a robust vision guided path tracking and hovering performance, the flight path guidance logic is combined in a multi conditional basis with the position estimation algorithm coupled with the vehicle attitude dynamics. An onboard flight test equipped with the developed realtime vision guided autopilot system is done using the rotary UAV system with full attitude control capability. Outdoor flight test demonstrated that the designed vision guided autopilot system succeeded in UAV's hovering on top of ground target within about several meters under geenral windy environment.

Separation of Dynamic RCS using Hough Transform in Multi-target Environment (허프 변환을 이용한 다표적 환경에서 동적 RCS 분리)

  • Kim, Yu-Jin;Choi, Young-Jae;Choi, In-Sik
    • The Journal of Korean Institute of Information Technology
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    • v.17 no.9
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    • pp.91-97
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    • 2019
  • When a radar tracks the warhead of a ballistic missile, decoys of a ballistic missile put a heavy burden on the radar resource management tracking the targets. To reduce this burden, it is necessary to be able to separate the signal of the warhead from the received dynamic radar cross section (RCS) signal on the radar. In this paper, we propose the method of separating the dynamic RCS of each target from the received signal by the Hough transform which extracts straight lines from the image. The micro motion of the targets was implemented using a 3D CAD model of the warhead and decoys. Then, we calculated the dynamic RCS from the 3D CAD model having micromotion and verified the performance by applying the proposed algorithm. Simulation results show that the proposed method can separate the signals of the warhead and decoys at the signal-to-noise ratio (SNR) of 10dB.

The Individual Discrimination Location Tracking Technology for Multimodal Interaction at the Exhibition (전시 공간에서 다중 인터랙션을 위한 개인식별 위치 측위 기술 연구)

  • Jung, Hyun-Chul;Kim, Nam-Jin;Choi, Lee-Kwon
    • Journal of Intelligence and Information Systems
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    • v.18 no.2
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    • pp.19-28
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    • 2012
  • After the internet era, we are moving to the ubiquitous society. Nowadays the people are interested in the multimodal interaction technology, which enables audience to naturally interact with the computing environment at the exhibitions such as gallery, museum, and park. Also, there are other attempts to provide additional service based on the location information of the audience, or to improve and deploy interaction between subjects and audience by analyzing the using pattern of the people. In order to provide multimodal interaction service to the audience at the exhibition, it is important to distinguish the individuals and trace their location and route. For the location tracking on the outside, GPS is widely used nowadays. GPS is able to get the real time location of the subjects moving fast, so this is one of the important technologies in the field requiring location tracking service. However, as GPS uses the location tracking method using satellites, the service cannot be used on the inside, because it cannot catch the satellite signal. For this reason, the studies about inside location tracking are going on using very short range communication service such as ZigBee, UWB, RFID, as well as using mobile communication network and wireless lan service. However these technologies have shortcomings in that the audience needs to use additional sensor device and it becomes difficult and expensive as the density of the target area gets higher. In addition, the usual exhibition environment has many obstacles for the network, which makes the performance of the system to fall. Above all these things, the biggest problem is that the interaction method using the devices based on the old technologies cannot provide natural service to the users. Plus the system uses sensor recognition method, so multiple users should equip the devices. Therefore, there is the limitation in the number of the users that can use the system simultaneously. In order to make up for these shortcomings, in this study we suggest a technology that gets the exact location information of the users through the location mapping technology using Wi-Fi and 3d camera of the smartphones. We applied the signal amplitude of access point using wireless lan, to develop inside location tracking system with lower price. AP is cheaper than other devices used in other tracking techniques, and by installing the software to the user's mobile device it can be directly used as the tracking system device. We used the Microsoft Kinect sensor for the 3D Camera. Kinect is equippedwith the function discriminating the depth and human information inside the shooting area. Therefore it is appropriate to extract user's body, vector, and acceleration information with low price. We confirm the location of the audience using the cell ID obtained from the Wi-Fi signal. By using smartphones as the basic device for the location service, we solve the problems of additional tagging device and provide environment that multiple users can get the interaction service simultaneously. 3d cameras located at each cell areas get the exact location and status information of the users. The 3d cameras are connected to the Camera Client, calculate the mapping information aligned to each cells, get the exact information of the users, and get the status and pattern information of the audience. The location mapping technique of Camera Client decreases the error rate that occurs on the inside location service, increases accuracy of individual discrimination in the area through the individual discrimination based on body information, and establishes the foundation of the multimodal interaction technology at the exhibition. Calculated data and information enables the users to get the appropriate interaction service through the main server.

Airborne Pulsed Doppler Radar Development (비행체 탑재 펄스 도플러 레이다 시험모델 개발)

  • Kwag, Young-Kil;Choi, Min-Su;Bae, Jae-Hoon;Jeon, In-Pyung;Yang, Ju-Yoel
    • Journal of Advanced Navigation Technology
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    • v.10 no.2
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    • pp.173-180
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    • 2006
  • An airborne radar is an essential aviation electronic system of the aircraft to perform various missions in all weather environments. This paper presents the design, development, and test results of the multi-mode pulsed Doppler radar system test model for helicopter-borne flight test. This radar system consists of 4 LRU units, which include ANTU(Antenna Unit), TRU(Tx Rx Unit), RSDU(Radar Signal & Data Processing Unit) and DISU(Display Unit). The developed technologies include the TACCAR processor, planar array antenna, TWTA transmitter, coherent I/Q detector, digital pulse compression, DSP based Doppler FFT filtering, adaptive CFAR, IMU, and tracking capability. The design performance of the developed radar system is verified through various helicopter-borne field tests including MTD (Moving Target Detector) capability for the Doppler compensation due to the moving platform motion.

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Scaling Attack Method for Misalignment Error of Camera-LiDAR Calibration Model (카메라-라이다 융합 모델의 오류 유발을 위한 스케일링 공격 방법)

  • Yi-ji Im;Dae-seon Choi
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.33 no.6
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    • pp.1099-1110
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    • 2023
  • The recognition system of autonomous driving and robot navigation performs vision work such as object recognition, tracking, and lane detection after multi-sensor fusion to improve performance. Currently, research on a deep learning model based on the fusion of a camera and a lidar sensor is being actively conducted. However, deep learning models are vulnerable to adversarial attacks through modulation of input data. Attacks on the existing multi-sensor-based autonomous driving recognition system are focused on inducing obstacle detection by lowering the confidence score of the object recognition model.However, there is a limitation that an attack is possible only in the target model. In the case of attacks on the sensor fusion stage, errors in vision work after fusion can be cascaded, and this risk needs to be considered. In addition, an attack on LIDAR's point cloud data, which is difficult to judge visually, makes it difficult to determine whether it is an attack. In this study, image scaling-based camera-lidar We propose an attack method that reduces the accuracy of LCCNet, a fusion model (camera-LiDAR calibration model). The proposed method is to perform a scaling attack on the point of the input lidar. As a result of conducting an attack performance experiment by size with a scaling algorithm, an average of more than 77% of fusion errors were caused.

Detection of Low-RCS Targets in Sea-Clutter using Multi-Function Radar (다기능 레이다를 이용한 저 RCS 해상표적 탐지성능 분석)

  • Lee, Myung-Jun;Kim, Ji-eun;Lee, Sang-Min;Jeon, Hyeon-Mu;Yang, Woo-Yong;Kim, Kyung-Tae
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.30 no.6
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    • pp.507-517
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    • 2019
  • Multi-function radar(MFR) is a system that uses various functions such as detection, tracking, and classification. To operate the functions in real-time, the detection stage in MFR usually uses radar signals for short measurement time. We can utilize several conventional detectors in the MFR system to detect low radar cross section maritime targets in the sea-clutter; however, the detectors, which have been developed to be effective for radar signals measured for a longer time, may be inappropriate for MFR. In this study, we proposed a modelling technique of sea-clutter short measurement time. We combined the modeled sea-clutter signal with the maritime-target signal, which was obtained by the numerical analysis method. Using this combined model, we exploited four independent detectors and analyzed the detection performances.

Design and Implementation of Radar Resource Management Algorithms for Airborne AESA Radar (항공기 탑재 능동 위상배열 레이더의 자원관리 알고리즘 설계 및 구현)

  • Roh, Ji-Eun;Chon, Sang-Mi;Ahn, Chang-Soo;Jang, Seong-Hoon
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.24 no.12
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    • pp.1190-1197
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    • 2013
  • AESA(Active Electronically Scanned Array radar) radar is able to instantaneously and adaptively position and control the beam, and such adaptive beam pointing of AESA radar enables to remarkably improve the multi-mission capability. For this reason, radar resource management(RRM) becomes new challenging issue. RRM is a technique efficiently allocating finite resources, such as energy and time to each task in an optimal and intelligent way. This paper deals with a design of radar resource management algorithms and simulator implemented main algorithms for development of airborne AESA radar. In addition, evaluation results show that developed radar system satisfies a main requirement about simultaneous multiple target tracking and detection by adopting proposed algorithms.