• 제목/요약/키워드: track objects

검색결과 257건 처리시간 0.029초

A Robust Algorithm for Tracking Non-rigid Objects

  • Kim, Jong-Ryul;Na, Hyun-Tae;Moon, Young-Shik
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2002년도 ITC-CSCC -1
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    • pp.141-144
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    • 2002
  • In this paper, we propose a new object tracking algorithm using deformed template and Level-Set theory, which is robust against background variation, object flexibility and occlusion. The proposed tracking algorithm consists of two steps. The first step is an estimation of object shape and location, on the assumption that the transformation of object can be approximately modeled by the affine transform. The second step is a refinement of the object shape to fit into the real object accurately, by using the potential energy map and the modified Level Set speed function. Experimental results show that the proposed algorithm can track non-rigid objects with large variation in the backgrounds.

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상호작용 조명 시스템을 위한 실시간 인체 움직임 및 객체 추적 (Real-time Human Behavior and Object Tracking for Interactive lighting System)

  • 박왕배;서융호;정다운;두경수;최종수
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2008년도 하계종합학술대회
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    • pp.937-938
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    • 2008
  • Spotlight system has been made use of art works on stage such as musical and performance etc. Currently, spotlight is controlled manually through the planned path in advance. Therefore, automatic control system is necessary for manipulating spotlight on stage. In this paper, we propose the system that detects to track the multiple objects and classifies those objects, also selects an object of those ones. The proposed method can be applied to the interactive stage spotlighting system(ISSS).

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깊이 화면을 이용한 움직임 객체의 추적 방법 (Tracking Method for Moving Object Using Depth Picture)

  • 권순각;김흥준
    • 한국멀티미디어학회논문지
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    • 제19권4호
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    • pp.774-779
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    • 2016
  • The conventional methods using color signal for tracking the movement of the object require a lot of calculation and the performance is not accurate. In this paper, we propose a method to effectively track the moving objects using the depth information from a depth camera. First, it separates the background and the objects based on the depth difference in the depth of the screen. When an object is moved, the depth value of the object becomes blurred because of the phenomenon of Motion Blur. In order to solve the Motion Blur, we observe the changes in the characteristics of the object (the area of the object, the border length, the roundness, the actual size) by its velocity. The proposed algorithm was implemented in the simulation that was applied directly to the tracking of a golf ball. We can see that the estimated value of the proposed method is accurate enough to be very close to the actual measurement.

Maritime Object Segmentation and Tracking by using Radar and Visual Camera Integration

  • Hwang, Jae-Jeong;Cho, Sang-Gyu;Lee, Jung-Sik;Park, Sang-Hyon
    • Journal of information and communication convergence engineering
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    • 제8권4호
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    • pp.466-471
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    • 2010
  • We have proposed a method to detect and track moving ships using position from Radar and image processor. Real-time segmentation of moving regions in image sequences is a fundamental step in the radar-camera integrated system. Algorithms for segmentation of objects are implemented by composing of background subtraction, morphologic operation, connected components labeling, region growing, and minimum enclosing rectangle. Once the moving objects are detected, tracking is only performed upon pixels labeled as foreground with reduced additional computational burdens.

사물 인터넷망을 위한 RFID 보안 프레임워크와 프로토콜 분석 (Analyses of RFID Security Framework and Protocol Supporting Internet of Things)

  • 김정태
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2014년도 추계학술대회
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    • pp.373-374
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    • 2014
  • Radio frequency identification system (RFID) is an automatic technology and aids machines or computers to identify objects, record metadata or control individual target through radio waves. Connecting RFID reader to the terminal of Internet, the readers can identify, track and monitor the objects attached with tags globally, automatically, and in real time, if needed. This is the so-called Internet of Things (IoT). RFID is often seen as a prerequisite for the IoT. This paper introduces amd surveyed the technologies of RFID and IoT, discusses the applications and challenges of RFID technology used in IoT.

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Creating Deep Learning-based Acrobatic Videos Using Imitation Videos

  • Choi, Jong In;Nam, Sang Hun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권2호
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    • pp.713-728
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    • 2021
  • This paper proposes an augmented reality technique to generate acrobatic scenes from hitting motion videos. After a user shoots a motion that mimics hitting an object with hands or feet, their pose is analyzed using motion tracking with deep learning to track hand or foot movement while hitting the object. Hitting position and time are then extracted to generate the object's moving trajectory using physics optimization and synchronized with the video. The proposed method can create videos for hitting objects with feet, e.g. soccer ball lifting; fists, e.g. tap ball, etc. and is suitable for augmented reality applications to include virtual objects.

사물 인터넷망에서의 RFID 응용 기술 및 보안 문제 분석 (Analyses of RFID Application and Its Security Problems Embedded in Internet of Things(IoT))

  • 김정태
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2014년도 춘계학술대회
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    • pp.473-474
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    • 2014
  • Radio frequency identification system (RFID) is an automatic technology and aids machines or computers to identify objects, record metadata or control individual target through wireless waves. Connecting RFID reader to the terminal of Internet, the readers can identify, track and monitor the objects attached with tags globally, automatically, and in real time, if needed. This is the so-called Internet of Things (IOT). RFID is often seen as a prerequisite for the IOT. This paper surveys the technologies of RFID and IOT, discusses the applications and challenges of RFID technology used in IoT.

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A Video Smoke Detection Algorithm Based on Cascade Classification and Deep Learning

  • Nguyen, Manh Dung;Kim, Dongkeun;Ro, Soonghwan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권12호
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    • pp.6018-6033
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    • 2018
  • Fires are a common cause of catastrophic personal injuries and devastating property damage. Every year, many fires occur and threaten human lives and property around the world. Providing early important sign for early fire detection, and therefore the detection of smoke is always the first step in fire-alarm systems. In this paper we propose an automatic smoke detection system built on camera surveillance and image processing technologies. The key features used in our algorithm are to detect and track smoke as moving objects and distinguish smoke from non-smoke objects using a convolutional neural network (CNN) model for cascade classification. The results of our experiment, in comparison with those of some earlier studies, show that the proposed algorithm is very effective not only in detecting smoke, but also in reducing false positives.

Combining an Edge-Based Method and a Direct Method for Robust 3D Object Tracking

  • Lomaliza, Jean-Pierre;Park, Hanhoon
    • 한국멀티미디어학회논문지
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    • 제24권2호
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    • pp.167-177
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    • 2021
  • In the field of augmented reality, edge-based methods have been popularly used in tracking textureless 3D objects. However, edge-based methods are inherently vulnerable to cluttered backgrounds. Another way to track textureless or poorly-textured 3D objects is to directly align image intensity of 3D object between consecutive frames. Although the direct methods enable more reliable and stable tracking compared to using local features such as edges, they are more sensitive to occlusion and less accurate than the edge-based methods. Therefore, we propose a method that combines an edge-based method and a direct method to leverage the advantages from each approach. Experimental results show that the proposed method is much robust to both fast camera (or object) movements and occlusion while still working in real time at a frame rate of 18 Hz. The tracking success rate and tracking accuracy were improved by up to 84% and 1.4 pixels, respectively, compared to using the edge-based method or the direct method solely.

인공지능 공간상의 다중객체 구분을 위한 컬러 패턴 인식과 추적 (Color Pattern Recognition and Tracking for Multi-Object Tracking in Artificial Intelligence Space)

  • 진태석
    • 한국산업융합학회 논문집
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    • 제27권2_2호
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    • pp.319-324
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    • 2024
  • In this paper, the Artificial Intelligence Space(AI-Space) for human-robot interface is presented, which can enable human-computer interfacing, networked camera conferencing, industrial monitoring, service and training applications. We present a method for representing, tracking, and objects(human, robot, chair) following by fusing distributed multiple vision systems in AI-Space. The article presents the integration of color distributions into particle filtering. Particle filters provide a robust tracking framework under ambiguous conditions. We propose to track the moving objects(human, robot, chair) by generating hypotheses not in the image plane but on the top-view reconstruction of the scene.