• Title/Summary/Keyword: Human Motion

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Automated Markerless Analysis of Human Gait Motion for Recognition and Classification

  • Yoo, Jang-Hee;Nixon, Mark S.
    • ETRI Journal
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    • v.33 no.2
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    • pp.259-266
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    • 2011
  • We present a new method for an automated markerless system to describe, analyze, and classify human gait motion. The automated system consists of three stages: I) detection and extraction of the moving human body and its contour from image sequences, ii) extraction of gait figures by the joint angles and body points, and iii) analysis of motion parameters and feature extraction for classifying human gait. A sequential set of 2D stick figures is used to represent the human gait motion, and the features based on motion parameters are determined from the sequence of extracted gait figures. Then, a k-nearest neighbor classifier is used to classify the gait patterns. In experiments, this provides an alternative estimate of biomechanical parameters on a large population of subjects, suggesting that the estimate of variance by marker-based techniques appeared generous. This is a very effective and well-defined representation method for analyzing the gait motion. As such, the markerless approach confirms uniqueness of the gait as earlier studies and encourages further development along these lines.

Feature Extraction Based on Hybrid Skeleton for Human-Robot Interaction (휴먼-로봇 인터액션을 위한 하이브리드 스켈레톤 특징점 추출)

  • Joo, Young-Hoon;So, Jea-Yun
    • Journal of Institute of Control, Robotics and Systems
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    • v.14 no.2
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    • pp.178-183
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    • 2008
  • Human motion analysis is researched as a new method for human-robot interaction (HRI) because it concerns with the key techniques of HRI such as motion tracking and pose recognition. To analysis human motion, extracting features of human body from sequential images plays an important role. After finding the silhouette of human body from the sequential images obtained by CCD color camera, the skeleton model is frequently used in order to represent the human motion. In this paper, using the silhouette of human body, we propose the feature extraction method based on hybrid skeleton for detecting human motion. Finally, we show the effectiveness and feasibility of the proposed method through some experiments.

Wireless Interface of Motion between Human and Robot

  • Jung, Seul;Jeon, Poong-Woo;Cho, Hyun-Taek;Jang, Pyung-Soo;Cho, Ki-Ho;Kim, Jeong-Gu;Song, Duck-Hee;Choi, Young-Kwon
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.59.4-59
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    • 2001
  • In this paper, wireless interface of the motion between human and robot is implemented. The idea is that if a human who is equiped with device including accelerometer and rate-gyro sensor move his/her arm, then the robot follows human motion. The robot is designed as wheeled type mobile robot with two link arms. The robot´s basic movements such as forward, backward, left, right movement can be controlled from foot sensor which human steps on. Arm movements can be controlled by arm motion of human motion. In order to detect human motion, sensor data analysis from gyro and accelerometer has to be done. Data from sensors are transferred through wireless communication to activate the robot.

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Generating 3-D Models of Human Motions by Motion Capture

  • Yamaguchi, I.;Tou, K.;Tan, J.K.;Ishikawa, S.;Naito, T.;Yokota, M.
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1629-1632
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    • 2003
  • A technique is presented for generating a compound human motion from its primitive motions obtained by a motion capture system. Some human fundamental motions are modeled in a 3-D way and registered as primitive motions. Because the factorization method is used for the motion capture, calibration of video cameras and connection of the motion in the direction of time is both unnecessary. Employing these motions, various compound human motions are generated by connecting the motions after having applied rotation and parallel transformation to them. Linear interpolation is done at the discontinuous boundary between primitive motions and smooth connection is achieved. Experimental results show satisfactory performance of the proposed technique. The technique may contribute to producing various complicated human motions without much effort using a strict motion capture system.

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Depth Camera-Based Posture Discrimination and Motion Interpolation for Real-Time Human Simulation (실시간 휴먼 시뮬레이션을 위한 깊이 카메라 기반의 자세 판별 및 모션 보간)

  • Lee, Jinwon;Han, Jeongho;Yang, Jeongsam
    • Korean Journal of Computational Design and Engineering
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    • v.19 no.1
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    • pp.68-79
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    • 2014
  • Human model simulation has been widely used in various industrial areas such as ergonomic design, product evaluation and characteristic analysis of work-related musculoskeletal disorders. However, the process of building digital human models and capturing their behaviors requires many costly and time-consuming fabrication iterations. To overcome the limitations of this expensive and time-consuming process, many studies have recently presented a markerless motion capture approach that reconstructs the time-varying skeletal motions from optical devices. However, the drawback of the markerless motion capture approach is that the phenomenon of occlusion of motion data occurs in real-time human simulation. In this study, we propose a systematic method of discriminating missing or inaccurate motion data due to motion occlusion and interpolating a sequence of motion frames captured by a markerless depth camera.

Realizing a Mixed Reality Space Guided by a Virtual Human;Creating a Virtual Human from Incomplete 3-D Motion Data

  • Abe, Shinsuke;Yamaguti, Iku;Tan, Joo Kooi;Ishikawa, Seiji
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1625-1628
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    • 2003
  • Recently the VR technique has evolved into a mixed reality (MR) technique, in which a user can observe a real world in front of him/her as well as virtual objects displayed. This has been realized by the employment of a see-through type HMD (S-HMD). We have been developing a mixed reality space employing the MR technique. The objective of our study is to realize a virtual human that acts as a man-machine interface in the real space. It is important in the study to create a virtual human acting naturally in front of a user. In order to give natural motions to the virtual human, we employ a developed motion capture technique. We have already created various 3-D human motion models by the motion capture technique. In this paper, we present a technique for creating a virtual human using a human model provided by a computer graphics software, 3D Studio Max(C). The main difficulty of this issue is that 3D Studio Max(C) claims 28 feature points for describing a human motion, but the used motion capture system assumes less number of feature points. Therefore a technique is proposed in the paper for producing motion data of 28 feature points from the motion data of less number of feature points or from incomplete motion data. Performance of the proposed technique was examined by observing visually the demonstration of some motions of a created virtual human and overall natural motions were realized.

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Kinematic and Dynamic Analyses of Human Arm Motion

  • Kim, Junghee;Cho, Sungho;Lee, Choongho;Han, Jaewoong;Hwang, Heon
    • Journal of Biosystems Engineering
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    • v.38 no.2
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    • pp.138-148
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    • 2013
  • Purpose: Determining an appropriate path is a top priority in order for a robot to maneuver in a dynamically efficient way especially in a pick-and-place task. In a non-standardized work environment, current robot arm executes its motion based on the kinematic displacements of joint variables, though resulting motion is not dynamically optimal. In this research we suggest analyzing and applying motion patterns of the human arm as an alternative to perform near optimum motion trajectory for arbitrary pick-and-place tasks. Methods: Since the motion of a human arm is very complicated and diverse, it was simplified into two links: one from the shoulder to the elbow, and the other from the elbow to the hand. Motion patterns were then divided into horizontal and vertical components and further analyzed using kinematic and dynamic methods. The kinematic analysis was performed based on the D-H parameters and the dynamic analysis was carried out to calculate various parameters such as velocity, acceleration, torque, and energy using the Newton-Euler equation of motion and Lagrange's equation. In an attempt to assess the efficacy of the analyzed human motion pattern it was compared to the virtual motion pattern created by the joint interpolation method. Results: To demonstrate the efficacy of the human arm motion mechanical and dynamical analyses were performed, followed by the comparison with the virtual robot motion path that was created by the joint interpolation method. Consequently, the human arm was observed to be in motion while the elbow was bent. In return this contributed to the increase of the manipulability and decrease of gravity and torque being exerted on the elbow. In addition, the energy required for the motion decreased. Such phenomenon was more apparent under vertical motion than horizontal motion patterns, and in shorter paths than in longer ones. Thus, one can minimize the abrasion of joints by lowering the stress applied to the bones, muscles, and joints. From the perspectives of energy and durability, the robot arm will be able to utilize its motor most effectively by adopting the motion pattern of human arm. Conclusions: By applying the motion pattern of human arm to the robot arm motion, increase in efficiency and durability is expected, which will eventually produce robots capable of moving in an energy-efficient manner.

Producing a Virtual Object with Realistic Motion for a Mixed Reality Space

  • Daisuke Hirohashi;Tan, Joo-Kooi;Kim, Hyoung-Seop;Seiji Ishikawa
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.153.2-153
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    • 2001
  • A technique is described for producing a virtual object with realistic motion. A 3-D human motion model is obtained by applying a developed motion capturing technique to a real human in motion. Factorization method is a technique for recovering 3-D shape of a rigid object from a single video image stream without using camera parameters. The technique is extended for recovering 3-D human motions. The proposed system is composed of three fixed cameras which take video images of a human motion. Three obtained image sequences are analyzed to yield measurement matrices at individual sampling times, and they are merged into a single measurement matrix to which the factorization is applied and the 3-D human motion is recovered ...

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A Joint Motion Planning Based on a Bio-Mimetic Approach for Human-like Finger Motion

  • Kim Byoung-Ho
    • International Journal of Control, Automation, and Systems
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    • v.4 no.2
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    • pp.217-226
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    • 2006
  • Grasping and manipulation by hands can be considered as one of inevitable functions to achieve the performances desired in humanoid operations. When a humanoid robot manipulates an object by his hands, each finger should be well-controlled to accomplish a precise manipulation of the object grasped. So, the trajectory of each joint required for a precise finger motion is fundamentally necessary to be planned stably. In this sense, this paper proposes an effective joint motion planning method for humanoid fingers. The proposed method newly employs a bio-mimetic concept for joint motion planning. A suitable model that describes an interphalangeal coordination in a human finger is suggested and incorporated into the proposed joint motion planning method. The feature of the proposed method is illustrated by simulation results. As a result, the proposed method is useful for a facilitative finger motion. It can be applied to improve the control performance of humanoid fingers or prosthetic fingers.

A Study on Characteristics of Inter-Articular Coordination of Human Fingers for Robotic Hands (로봇 손을 위한 인간 손가락의 관절간 운동특성 고찰)

  • Kim Byoung-Ho
    • Journal of the Korean Society for Precision Engineering
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    • v.23 no.7 s.184
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    • pp.67-75
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    • 2006
  • One of challenging topics for humanoid hands is to modulate a human-like motion of humanoid fingers handling an object. To this end, recognizing the motion behavior of human fingers is very important aspect. Based on this concept, this paper identifies the .joint trajectories of human fingers for an operation of hand opening and closing, and specifies an empirical model that coordinates an inter-articular relationship of human fingers doing the given motion. It is expected that the inter-articular model presented in this paper is applicable for humanoid fingers to mimic the natural motion of human fingers.