• Title/Summary/Keyword: Tracking Algorithm

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Robust Tracking Algorithm for Moving Object using Kalman Filter and Variable Search Window Technique (칼만 필터와 가변적 탐색 윈도우 기법을 적용한 강인한 이동 물체 추적 알고리즘)

  • Kim, Young-Kyun;Hyeon, Byeong-Yong;Cho, Young-Wan;Seo, Ki-Sung
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.7
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    • pp.673-679
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    • 2012
  • This paper introduces robust tracking algorithm for fast and erratic moving object. CAMSHIFT algorithm has less computation and efficient performance for object tracking. However, the method fails to track a object if it moves out of search window by fast velocity and/or large movement. The size of the search window in CAMSHIFT algorithm should be selected manually also. To solve these problems, we propose an efficient prediction technique for fast movement of object using Kalman Filter with automatic initial setting and variable configuration technique for search window. The proposed method is compared to the traditional CAMSHIFT algorithm for searching and tracking performance of objects on test image frames.

A Modified Expansion-Contraction Method for Mobile Object Tracking in Video Surveillance: Indoor Environment

  • Kang, Jin-Shig
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.13 no.4
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    • pp.298-306
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    • 2013
  • Recent years have witnessed a growing interest in the fields of video surveillance and mobile object tracking. This paper proposes a mobile object tracking algorithm. First, several parameters such as object window, object area, and expansion-contraction (E-C) parameter are defined. Then, a modified E-C algorithm for multiple-object tracking is presented. The proposed algorithm tracks moving objects by expansion and contraction of the object window. In addition, it includes methods for updating the background image and avoiding occlusion of the target image. The validity of the proposed algorithm is verified experimentally. For example, the first scenario traces the path of two people walking in opposite directions in a hallway, whereas the second one is conducted to track three people in a group of four walkers.

Intelligent Multimode Target Tracking Using Fuzzy Logic (퍼지 로직을 이용한 지능적인 다중모드 목표물 추적)

  • 조재수;박동조
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.10a
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    • pp.468-473
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    • 1998
  • An intelligent multimode target tracking algorithm using fuzzy logic is presented. Multimode tracking represents a synergistic approach that utilizes a variety of tracking techniques(centroid, correlation, etc.) to overcome the limitations inherent in any single-mode tracker. The design challenge for this type of multimode tracker is the data fusion algorithm. designs for this algorithm are based on heuristic rather than analytical approaches. A correlation-tracking algorithm seeks to align the incoming target image with a reference in age of the target, but has a critical problem, so called drift phenomenon. In this paper we will suggest a robust correlation tracker with gradient preprocessor combined by centroid algorithm to overcome the drift problem.

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Acoustic Target of Interest Tracking Algorithm Using Classification Feedback (표적 식별 정보 피드백을 통한 관심 음향 표적 추적 기법)

  • Choi, Kiseok
    • The Journal of the Acoustical Society of Korea
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    • v.33 no.4
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    • pp.225-231
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    • 2014
  • This paper suggests an algorithm to improve the tracking performance for an underwater acoustic target using the feedback information of acoustic feature of a target. While conventional tracking algorithms use detected acoustic signals only, the proposed algorithm uses detected acoustic signals and target feature information as well. Since the proposed algorithm tracks only the selected measurements using target feature information, it prevents onset of unnecessary tracks and improves tracking performance for target of interest. Furthermore, it optimizes tracking parameters for the target of interest and guarantees robustness and consistency of the track. Some simulations are performed to demonstrate the improved tracking performance of the proposed algorithm.

Feature point extraction using scale-space filtering and Tracking algorithm based on comparing texturedness similarity (스케일-스페이스 필터링을 통한 특징점 추출 및 질감도 비교를 적용한 추적 알고리즘)

  • Park, Yong-Hee;Kwon, Oh-Seok
    • Journal of Internet Computing and Services
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    • v.6 no.5
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    • pp.85-95
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    • 2005
  • This study proposes a method of feature point extraction using scale-space filtering and a feature point tracking algorithm based on a texturedness similarity comparison, With well-defined operators one can select a scale parameter for feature point extraction; this affects the selection and localization of the feature points and also the performance of the tracking algorithm. This study suggests a feature extraction method using scale-space filtering, With a change in the camera's point of view or movement of an object in sequential images, the window of a feature point will have an affine transform. Traditionally, it is difficult to measure the similarity between correspondence points, and tracking errors often occur. This study also suggests a tracking algorithm that expands Shi-Tomasi-Kanade's tracking algorithm with texturedness similarity.

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Performance Improvement for Tracking Small Targets (고기동 표적 추적 성능 개선을 위한 연구)

  • Jung, Yun-Sik;Kim, Kyung-Su;Song, Taek-Lyul
    • Journal of Institute of Control, Robotics and Systems
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    • v.16 no.11
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    • pp.1044-1052
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    • 2010
  • In this paper, a new realtime algorithm called the RTPBTD-HPDAF (Recursive Temporal Profile Base Target Detection with Highest Probability Data Association Filter) is presented for tracking fast moving small targets with IIR (Imaging Infrared) sensor systems. Spatial filter algorithms are mainly used for target in IIR sensor system detection and tracking however they often generate high density clutter due to various shapes of cloud. The TPBTD (Temporal Profile Base Target Detection) algorithm based on the analysis of temporal behavior of individual pixels is known to have good performance for detection and tracking of fast moving target with suppressing clutter. However it is not suitable to detect stationary and abruptly maneuvering targets. Moreover its computational load may not be negligible. The PTPBTD-HPDAF algorithm proposed in this paper for real-time target detection and tracking is shown to be computationally cheap while it has benefit of tracking targets with abrupt maneuvers. The performance of the proposed RTPBTD-HPDAF algorithm is tested and compared with the spatial filter with HPDAF algorithm for run-time and track initiation at real IIR video.

Path Planning and Tracking for Mobile Robots Using An Improved Distance Transform Algorithm (개선된 거리변환 알고리즘을 이용한 이동 로봇의 경로 계획 및 추적)

  • Park Jin-Hyun;Park Gi-Hyung;Choi Young-Kiu
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.9 no.4
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    • pp.782-791
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    • 2005
  • In this paper, path planning and tracking problems are mentioned to guarantee efficient and safe navigation of autonomous mobile robots. We focus on the path planning and also deal with the path tracking and obstacle avoidance. We improved the conventional distance transform (DT) algorithm for the path planning. Using the improved DT algorithm, we obtain paths with shorter distances compared to the conventional DT algorithm. In the stage of the Path tracking, we employ the fuzzy logic controller to conduct the path tracking behavior and obstacle avoidance behavior. Through computer simulation studies, we show the effectiveness of the Nosed navigational algorithm for autonomous mobile robots.

Path Planning and Tracking for Mobile Robots Using An Improved Distance Transform Algorithm (개선된 거리변환 알고리즘을 이용한 이동 로봇의 경로 계획 및 추적)

  • Park, Jin-Hyun;Park, Gi-Hyung;Choi, Young-Kiu
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • v.9 no.1
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    • pp.295-299
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    • 2005
  • In this paper, path planning and tracking problems are mentioned to guarantee efficient and safe navigation of autonomous mobile robots. We focus on the path planning and also deal with the path tracking and obstacle avoidance. We improved the conventional distance transform (DT) algorithm for the path planning. Using the improved DT algorithm, we obtain paths with shorter distances compared to the conventional DT algorithm. In the stage of the path tracking, we employ the fuzzy logic controller to conduct the path tracking behavior and obstacle avoidance behavior. Through computer simulation studies, we show the effectiveness of the proposed navigational algorithm for autonomous mobile robots.

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Development of a New 2-Frame Particle Tracking Algorithm Using Match Probability (일치확률방식의 2-프레임 PTV 알고리듬 개발)

  • 백승조;이상준
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.19 no.7
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    • pp.1741-1748
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    • 1995
  • A new particle tracking algorithm using the concept of match probability between two consequent image frames has been developed to obtain an instantaneous 2-dimensional velocity field. A computer simulation has been carried out to check the performance and usefulness of the developed algorithm by comparing with the conventional 4-frame Particle Tracking Velocimetry(PTV) method. As a result the newly developed algorithm shows very good performance. Although the major part of the developed algorithm is time-consuming iterative updating routine of match probability, computational elapse time to get the resonable results is a very short compared with the 4-frame PTv.Additionally, the present 2-frame PTV algorithm recovers more velocity vectors and has higher dynamic range and lower error ratio compared with the conventional 4-frame PTV.

Motion planning of a robot manipulator for conveyor tracking (컨베이어 추적을 위한 로보트 매니퓰레이터의 동작 계획)

  • 박태형;이범희;고명삼
    • 제어로봇시스템학회:학술대회논문집
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    • 1989.10a
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    • pp.154-159
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    • 1989
  • This paper presents a motion planning algorithm for conveyor tracking. We formulate the problem as the linear quadratic tracking problem in optimal control theory and solve it through dynamic programming. In the proposed algorithm, the steady-state tracking error is eliminated completely, and the joint torque, velocity, acceleration, and jerks are considered as some constraints. Numerical examples are then presented to demonstrate the utility of the proposed motion planning algorithm.

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