• Title/Summary/Keyword: relative human body coordinate system

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Interactive 3D Pattern Design Using Real-time Pattern Deformation and Relative Human Body Coordinate System (실시간 패턴 변형과 인체 상대좌표계를 이용한 대화형 3D 패턴 디자인)

  • Sul, In-Hwan;Han, Hyun-Sook;Nam, Yun-Ja;Park, Chang-Kyu
    • Fashion & Textile Research Journal
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    • v.12 no.5
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    • pp.582-590
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    • 2010
  • Garment design needs an iterative manipulation of 2D patterns to generate a final sloper. Traditionally there have been two kinds of design methodologies such as the flat pattern method and the pattern draping method. But today, it is possible to combine the advantages from the two methods due to the realistic cloth simulation techniques. We devised a new garment design system which starts from 3D initial drape simulation result and then modifies the garment by editing the 2D flat patterns synchronously. With this interactive methodology using real-time pattern deformation technique, the designer can freely change a pattern shape by watching its 3D outlook in real-time. Also the final garment data were given relative coordinates with respect to the human anthropometric feature points detected by an automatic body feature detection algorithm. Using the relative human body coordinate system, the final garments can be re-used to an arbitrary body data without repositioning in the drape simulation. A female shirt was used for an example and a 3D body scan data was used for an illustration of the feature point detection algorithm.

Human Activity Recognition with LSTM Using the Egocentric Coordinate System Key Points

  • Wesonga, Sheilla;Park, Jang-Sik
    • Journal of the Korean Society of Industry Convergence
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    • v.24 no.6_1
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    • pp.693-698
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    • 2021
  • As technology advances, there is increasing need for research in different fields where this technology is applied. On of the most researched topic in computer vision is Human activity recognition (HAR), which has widely been implemented in various fields which include healthcare, video surveillance and education. We therefore present in this paper a human activity recognition system based on scale and rotation while employing the Kinect depth sensors to obtain the human skeleton joints. In contrast to previous approaches that use joint angles, in this paper we propose that each limb has an angle with the X, Y, Z axes which we employ as feature vectors. The use of the joint angles makes our system scale invariant. We further calculate the body relative direction in the egocentric coordinates in order to provide the rotation invariance. For the system parameters, we employ 8 limbs with their corresponding angles each having the X, Y, Z axes from the coordinate system as feature vectors. The extracted features are finally trained and tested with the Long short term memory (LSTM) Network which gives us an average accuracy of 98.3%.

A Review on the Mechanism of Human Postural Control (인간의 자세조절 메커니즘에 대한 연구)

  • Lee, Dong-Woo
    • Korean Journal of Applied Biomechanics
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    • v.15 no.1
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    • pp.45-61
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    • 2005
  • Stance is defined as any state in which the total mass of the body is supported by the feet. In order to maintain stance, the sum of gravito-inertial forces acting on the body must be registered by equal and opposite forces at the region of contact between the organism and the support surface. Balance is controlled by applying forces to the surface of support so as to maintain the body's center of mass vertically above the feet. for a muIti-segment organism, there can be a variety of ways in which balance can be controlled, since movements of different body segments can have similar effects on the control of balance. In general, the organism tends to have a body configuration that is aligned with gravito-inertial force when there are no external forces acting on it. If any segments of the body are not aligned with gravito-inertial force vector, a torque on that segment would tend to move the body's center of mass. The maintenance of postural stability is accomplished in humans by a complex neural control system. This requires organizing integrating and acting upon visual, vestibular, and somatosensory input, providing orientation information to the postural control system. The information necessary to control and coordinate movement is provided by the visual sense of eye position with respect to the surrounding surface layout, the vestibular sense of head orientation in the gravito-inertial space, and the somatic sense of body segment position relative to one another and to the support surface. In this study, perception and action capability was examined from various points of view. The underlying assumption of the study was that the change of postural configuration could be effected by organism, environment and task goal.