• Title/Summary/Keyword: Human Tracking

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Markless System of Using Hand Tracking (핸드 트레킹을 이용한 Markerless 시스템)

  • Ban, Kyeong-Jin;Kim, Jong-Chan;Kim, Kyeong-Og;Kim, Eung-Kon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2010.05a
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    • pp.683-685
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    • 2010
  • Augmented reality is a technology for showing virtual objects overlapped with the real world as seen from the eyes of users. Studies are being conducted on effective communication methods using hand movements in augmented reality. Hand movements are an important means of human communication along with writing and voice. Space arrangement technology and hand tracking technology using markers to acquire virtual information in augmented reality have many limitations. This paper proposes tracking hand area for augmented object. The augmented objects change viewpoints by hand positions which improves the sense of three dimensions and immersion.

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A Study on High Speed Face Tracking using the GPGPU-based Depth Information (GPGPU 기반의 깊이 정보를 이용한 고속 얼굴 추적에 대한 연구)

  • Kim, Woo-Youl;Seo, Young-Ho;Kim, Dong-Wook
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.17 no.5
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    • pp.1119-1128
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    • 2013
  • In this paper, we propose an algorithm to detect and track the human face with a GPU-based high speed. Basically the detection algorithm uses the existing Adaboost algorithm but the search area is dramatically reduced by detecting movement and skin color region. Differently from detection process, tracking algorithm uses only depth information. Basically it uses a template matching method such that it searches a matched block to the template. Also, In order to fast track the face, it was computed in parallel using GPU about the template matching. Experimental results show that the GPU speed when compared with the CPU has been increased to up to 49 times.

Robust Location Tracking Using a Double Layered Particle Filter (이중 구조의 파티클 필터를 이용한 강인한 위치추적)

  • Yun, Keun-Ho;Kim, Dai-Jin;Bang, Sung-Yang
    • Journal of KIISE:Software and Applications
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    • v.33 no.12
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    • pp.1022-1030
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    • 2006
  • The location awareness is an important part of many ubiquitous computing systems, but a perfect location system does not exist yet in spite of many researches. Among various location tracking systems, we choose the RFID system due to its wide applications. However, the sensed RSSI signal is too sensitive to the direction of a RFID reader antenna, the orientation of a RFID tag, the human interference, and the propagation media situation. So, the existing location tracking method in spite of using the particle filter is not working well. To overcome this shortcoming, we suggest a robust location tracking method with a double layered structure, where the first layer coarsely estimates a tag's location in the block level using a regression technique or the SVM classifier and the second layer precisely computes the tag's location, velocity and direction using the particle filter technique. Its layered structure improves the location tracking performance by restricting the moving degree of hidden variables. Many extensive experiments show that the proposed location tracking method is so precise and robust to be a good choice for implementing the location estimation of a person or an object in the ubiquitous computing. We also validate the usefulness of the proposed location tracking method by implementing it for a real-time people monitoring system in a noisy and complicate workplace.

Bayesian Network Model for Human Fatigue Recognition (피로 인식을 위한 베이지안 네트워크 모델)

  • Lee Young-sik;Park Ho-sik;Bae Cheol-soo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.30 no.9C
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    • pp.887-898
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    • 2005
  • In this paper, we introduce a probabilistic model based on Bayesian networks BNs) for recognizing human fatigue. First of all, we measured face feature information such as eyelid movement, gaze, head movement, and facial expression by IR illumination. But, an individual face feature information does not provide enough information to determine human fatigue. Therefore in this paper, a Bayesian network model was constructed to fuse as many as possible fatigue cause parameters and face feature information for probabilistic inferring human fatigue. The MSBNX simulation result ending a 0.95 BN fatigue index threshold. As a result of the experiment, when comparisons are inferred BN fatigue index and the TOVA response time, there is a mutual correlation and from this information we can conclude that this method is very effective at recognizing a human fatigue.

Vision-based recognition of a simple non-verbal intent representation by head movements (고개운동에 의한 단순 비언어 의사표현의 비전인식)

  • Yu, Gi-Ho;No, Deok-Su;Lee, Seong-Cheol
    • Journal of the Ergonomics Society of Korea
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    • v.19 no.1
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    • pp.91-100
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    • 2000
  • In this paper the intent recognition system which recognizes the human's head movements as a simple non-verbal intent representation is presented. The system recognizes five basic intent representations. i.e., strong/weak affirmation. strong/weak negation, and ambiguity by image processing of nodding or shaking movements of head. The vision system for tracking the head movements is composed of CCD camera, image processing board and personal computer. The modified template matching method which replaces the reference image with the searched target image in the previous step is used for the robust tracking of the head movements. For the improvement of the processing speed, the searching is performed in the pyramid representation of the original image. By inspecting the variance of the head movement trajectories. we can recognizes the two basic intent representations - affirmation and negation. Also, by focusing the speed of the head movements, we can see the possibility which recognizes the strength of the intent representation.

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Livestock Theft Detection System Using Skeleton Feature and Color Similarity (골격 특징 및 색상 유사도를 이용한 가축 도난 감지 시스템)

  • Kim, Jun Hyoung;Joo, Yung Hoon
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.67 no.4
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    • pp.586-594
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    • 2018
  • In this paper, we propose a livestock theft detection system through moving object classification and tracking method. To do this, first, we extract moving objects using GMM(Gaussian Mixture Model) and RGB background modeling method. Second, it utilizes a morphology technique to remove shadows and noise, and recognizes moving objects through labeling. Third, the recognized moving objects are classified into human and livestock using skeletal features and color similarity judgment. Fourth, for the classified moving objects, CAM (Continuously Adaptive Meanshift) Shift and Kalman Filter are used to perform tracking and overlapping judgment, and risk is judged to generate a notification. Finally, several experiments demonstrate the feasibility and applicability of the proposed method.

Hand gesture recognition for player control

  • Shi, Lan Yan;Kim, Jin-Gyu;Yeom, Dong-Hae;Joo, Young-Hoon
    • Proceedings of the KIEE Conference
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    • 2011.07a
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    • pp.1908-1909
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    • 2011
  • Hand gesture recognition has been widely used in virtual reality and HCI (Human-Computer-Interaction) system, which is challenging and interesting subject in the vision based area. The existing approaches for vision-driven interactive user interfaces resort to technologies such as head tracking, face and facial expression recognition, eye tracking and gesture recognition. The purpose of this paper is to combine the finite state machine (FSM) and the gesture recognition method, in other to control Windows Media Player, such as: play/pause, next, pervious, and volume up/down.

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Drowsiness Sensing System by Detecting Eye-blink on Android based Smartphones

  • Vununu, Caleb;Seung, Teak-Young;Moon, Kwang-Seok;Lee, Suk-Hwan;Kwon, Ki-Ryong
    • Journal of Korea Multimedia Society
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    • v.19 no.5
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    • pp.797-807
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    • 2016
  • The discussion in this paper aims to introduce an approach to detect drowsiness with Android based smartphones using the OpenCV platform tools. OpenCV for Android actually provides powerful tools for real-time body's parts tracking. We discuss here about the maximization of the accuracy in real-time eye tracking. Then we try to develop an approach for detecting eye blink by analyzing the structure and color variations of human eyes. Finally, we introduce a time variable to capture drowsiness.

Personal digital assistants: Essential tools for preparing dietetics professionals to use new-generation information technology

  • Jang, Mi-Young;Song, Won-O.
    • Nutrition Research and Practice
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    • v.1 no.1
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    • pp.42-45
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    • 2007
  • Rapid integration of information technology into health care systems has included the use of highly portable systems-in particular, personal digital assistants (PDAs). With their large built-in memories, fast processors, wireless connectivity, multimedia capacity, and large library of applications, PDAs have been widely adopted by physicians and nurses for patient tracking, disease management, medical references and drug information, enhancing quality of health care. Many health-related PDA applications are available to both dietetics professionals and clients. Dietetics professionals can effectively use PDAs for client tracking and support, accessing to hospital database or information, and providing better self-monitoring tools to clients. Internship programs for dietetics professionals should include training in the use of PDAs and their dietetics applications, so that new practitioners can stay abreast of this rapidly evolving technology. Several considerations to keep in mind in selecting a PDA and its applications are discussed.

39.3 Hyper-reality Head Dome Projector $^{TM}$(HDP) for future displays

  • Okumura, Haruhiko;Sasaki, Takashi;Hotta, Aira;Okada, Naotada
    • 한국정보디스플레이학회:학술대회논문집
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    • 2008.10a
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    • pp.1331-1334
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    • 2008
  • In this paper, we developed a novel hyperreality display called the Head Dome Projector (HDP). The HDP is a head-mounted display consisting of a dome-shaped screen with a very small radius of 40 cm, a mobile projector with ultra-wide projection lens and LED light sources. The main feature of the HDP is very wide viewing angle of 160 degrees horizontally by 120 degrees vertically comparable to the human visual field of view without head tracking and 360 degrees by 360 degrees with head tracking. According to our subjective evaluation comparing the HDP with a flat-panel display (FPD), the HDP realizes hyperreality 2.5 points higher than that realized by an FPD in the case of ${\pm}5$ level evaluation for HD motion images.

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