• 제목/요약/키워드: Movement Recognition

검색결과 493건 처리시간 0.022초

박물관 전시공간에서의 주시특성에 관한 기초적 연구 - 부산박물관을 중심으로 - (A Study on the Basic Research of Eye Fixation in the Space of Exhibition at A Museum - Focus on the Busan Museum -)

  • 유재엽;박혜경;임채진
    • 한국실내디자인학회논문집
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    • 제20권2호
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    • pp.64-71
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    • 2011
  • There are a method to analyze reactions or psychological condition and a method to observe visitor's behavioral reaction as methods to measure and evaluate humans' recognition behavior reaction of humans. The measure of the eye movement as a method to living body's reaction and psychological condition has an advantage to measure the information acceptance reaction of view recognition of the stimulus of view composition factors which has been used since a long time ago in other research areas, but almost not studies have been made on the exhibition views in museums. Therefore, on the premise of such recognition, this study aimed at obtaining various types of information through vision angles of visitor in exhibition space of an museum and judging space information, at measuring the condition of information acceptance through attention experiments and observation investigation of and finding out the disposition and characteristics so as to verify the relationship between the exhibition space and exhibition Method.

한국과 일본 대학교 구성원의 그린캠퍼스 인식 비교 연구 (Recognition Comparison for Green Campus System in Korean and Japanese Universities)

  • 구자건;조용일;이승용;김주향;정종철;김용범
    • 한국환경교육학회지:환경교육
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    • 제25권2호
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    • pp.180-194
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    • 2012
  • Green campus means the environmentally-conscious universities that are trying to increase campus sustainability by reducing carbon emissions, expanding eco-friendly activities. This study was carried out to compare the recognition level on green campus between Korea and Japan universities. For investigating the recognition level of students and faculties on green campus, the questionnaire surveys were conducted by personal interviews in Korea and Japan, separately. The 40% and 68% respondents in Korean A and B universities, respectively, pointed out the energy issue as one of the serious environmental problems while the corresponding ratio among Japanese respondents was 44% and 34%. The participation intention for green campus movement in Japanese universities was higher than Korean universities. The 70% or 52% of Korean students in A and B universities, respectively, replied that they did not participate the green campus movement. It is needed to strengthen the educational program to achieve the sustainability of campus in Korea.

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다층 퍼셉트론을 이용한 유해물질 유입에 따른 송사리의 행동 반응 분석 및 인식 (Analysis and Recognition of Behavior of Medaka in Response to Toxic Chemical Inputs by using Multi-Layer Perceptron)

  • 김철기;김광백;차의영
    • 한국멀티미디어학회논문지
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    • 제6권6호
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    • pp.1062-1070
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    • 2003
  • 본 논문에서는 자동 추적 시스템을 이용하여 반자연적인 조건에서 화학 약물의 아치사량 투석에 반응하는 수중 생물중 하나인 물고기(송사리)의 행동을 관찰하였다. 결과의 분석을 위하여, 약물 투여 전의 대표적인 행동을 패턴 A로 정의하였으며, 약물 투여 후의 대표적인 행동을 패턴 B로 정의하였다. 실험 결과, 패턴 B가 약물 투여 후에 빈번하게 관찰되는 반면, 패턴 A는 약물 투여 전에 많이 관찰되었다. 또한, 물고기의 움직임 패턴을 자동으로 탐지하기 위하여 대표 패턴들을 인공신경망의 학습을 위하여 추출하였다. 독성 물질(다이아지논) 투여 후 패턴 B에 대한 평균 탐지율은 크게 증가하였으나, 패턴 A에 대한 탐지율은 크게 감소함을 볼 수 있었다 본 논문에서는 지표종의 행동 모니터링을 통하여 환경에서 독성 물질의 존재를 탐지하는 방법으로 인공 신경망의 적용을 보여주고 있다.

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Improved DT Algorithm Based Human Action Features Detection

  • Hu, Zeyuan;Lee, Suk-Hwan;Lee, Eung-Joo
    • 한국멀티미디어학회논문지
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    • 제21권4호
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    • pp.478-484
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    • 2018
  • The choice of the motion features influences the result of the human action recognition method directly. Many factors often influence the single feature differently, such as appearance of the human body, environment and video camera. So the accuracy of action recognition is restricted. On the bases of studying the representation and recognition of human actions, and giving fully consideration to the advantages and disadvantages of different features, the Dense Trajectories(DT) algorithm is a very classic algorithm in the field of behavior recognition feature extraction, but there are some defects in the use of optical flow images. In this paper, we will use the improved Dense Trajectories(iDT) algorithm to optimize and extract the optical flow features in the movement of human action, then we will combined with Support Vector Machine methods to identify human behavior, and use the image in the KTH database for training and testing.

A Deep Learning Algorithm for Fusing Action Recognition and Psychological Characteristics of Wrestlers

  • Yuan Yuan;Yuan Yuan;Jun Liu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제17권3호
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    • pp.754-774
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    • 2023
  • Wrestling is one of the popular events for modern sports. It is difficult to quantitatively describe a wrestling game between athletes. And deep learning can help wrestling training by human recognition techniques. Based on the characteristics of latest wrestling competition rules and human recognition technologies, a set of wrestling competition video analysis and retrieval system is proposed. This system uses a combination of literature method, observation method, interview method and mathematical statistics to conduct statistics, analysis, research and discussion on the application of technology. Combined the system application in targeted movement technology. A deep learning-based facial recognition psychological feature analysis method for the training and competition of classical wrestling after the implementation of the new rules is proposed. The experimental results of this paper showed that the proportion of natural emotions of male and female wrestlers was about 50%, indicating that the wrestler's mentality was relatively stable before the intense physical confrontation, and the test of the system also proved the stability of the system.

EOG와 마커인식을 이용한 착용형 사용자 인터페이스 (Wearable User Interface based on EOG and Marker Recognition)

  • 강선경;정성태;이상설
    • 한국컴퓨터정보학회논문지
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    • 제11권6호
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    • pp.133-141
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    • 2006
  • 최근 많은 착용형 컴퓨터가 개발되었지만, 아직도 입력 및 출력 관점에서 보면 사용자 인터페이스에 많은 문제를 가지고 있다. 본 논문에서는 EOG 감지 회로와 마커 인식에 기반한 착용형 사용자 인터페이스를 제안한다. 제안된 사용자 인터페이스에서 EOG 감지 회로는 지시 장치로 사용되는데, 눈 주위의 전위차를 감지함으로써 눈동자의 움직임을 추적한다. 사용자가 다루고자 하는 객체는 사람이 인지 가능한 마커로 표시되며 마커 인식 시스템은 카메라 영상으로부터 마커를 검출하고 인식한다. 마커가 인식되면 해당하는 객체에 대한 속성창과 마커 창이 HMD에 디스플레이되고 사용자는 원하는 속성이나 메소드를 선택함으로써 객체를 다루게 된다. EOG 감지 회로와 마커 인식 시스템을 이용함으로써 사용자는 착용형 컴퓨팅 환경에서 눈동자의 움직임만으로 객체의 조작을 손쉽게 수행할 수 있다.

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Quantitative Analysis of C. elegans Mutant Type Using Movement and Reversal Features

  • Nah Won;Baek Joong-Hwan
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2004년도 ICEIC The International Conference on Electronics Informations and Communications
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    • pp.417-420
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    • 2004
  • Caenorhabditis (C) elegans is often used in genetic analysis in neuroscience because its simple organism; an adult hermaphrodite contains only 302 neuron. So the worm is often used to study of cancer, alzheimer disease, aging, etc. To analysis mutant type of the worm, an experienced observer was able to subjectively before, but requirements for objective analysis are now increasing. For this reason, we use automated tracking systems to extract global movement coordinate of the worm. In this paper, we extract features, which are related on reversal and movement of the worm. Using these features, we quantitatively analysis 6 type mutant by movement and reversal characteristic.

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Study on Method of Measurement for Stress-Easing Viewing Urban Greenery

  • Yamamoto, Satoshi;Iwasaki, Yutaka
    • 한국조경학회:학술대회논문집
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    • 한국조경학회 2007년도 Journal of Landscape Architecture in Asia Vol.3
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    • pp.84-88
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    • 2007
  • When people recognize a landscape, they first need to see it for a definite period time. This study clarified the way green space in a landscape is recognized using eye movement analysis, and evaluated the Pffi9bility for quantifying stress-reducing effects of seeing a landscape. The results of the experiments on eye movement analysis suggest that the way of recognizing green space in a landscape may depend on a ratio of the amount of scenic greenery in a landscape, color and greenery layout. Especially, this study also suggests that the possibility of the greenery layout guiding eye movement could be verified by conducting a study on planting patterns. In addition, the results of the experiments for quantifying stress-reducing substances found that it is likely that a green space in an urban area has stress-reducing effects.

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Spatio-temporal Semantic Features for Human Action Recognition

  • Liu, Jia;Wang, Xiaonian;Li, Tianyu;Yang, Jie
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제6권10호
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    • pp.2632-2649
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    • 2012
  • Most approaches to human action recognition is limited due to the use of simple action datasets under controlled environments or focus on excessively localized features without sufficiently exploring the spatio-temporal information. This paper proposed a framework for recognizing realistic human actions. Specifically, a new action representation is proposed based on computing a rich set of descriptors from keypoint trajectories. To obtain efficient and compact representations for actions, we develop a feature fusion method to combine spatial-temporal local motion descriptors by the movement of the camera which is detected by the distribution of spatio-temporal interest points in the clips. A new topic model called Markov Semantic Model is proposed for semantic feature selection which relies on the different kinds of dependencies between words produced by "syntactic " and "semantic" constraints. The informative features are selected collaboratively based on the different types of dependencies between words produced by short range and long range constraints. Building on the nonlinear SVMs, we validate this proposed hierarchical framework on several realistic action datasets.

Hand Gesture Recognition using Optical Flow Field Segmentation and Boundary Complexity Comparison based on Hidden Markov Models

  • Park, Sang-Yun;Lee, Eung-Joo
    • 한국멀티미디어학회논문지
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    • 제14권4호
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    • pp.504-516
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    • 2011
  • In this paper, we will present a method to detect human hand and recognize hand gesture. For detecting the hand region, we use the feature of human skin color and hand feature (with boundary complexity) to detect the hand region from the input image; and use algorithm of optical flow to track the hand movement. Hand gesture recognition is composed of two parts: 1. Posture recognition and 2. Motion recognition, for describing the hand posture feature, we employ the Fourier descriptor method because it's rotation invariant. And we employ PCA method to extract the feature among gesture frames sequences. The HMM method will finally be used to recognize these feature to make a final decision of a hand gesture. Through the experiment, we can see that our proposed method can achieve 99% recognition rate at environment with simple background and no face region together, and reduce to 89.5% at the environment with complex background and with face region. These results can illustrate that the proposed algorithm can be applied as a production.