• Title/Summary/Keyword: Kinect Depth Sensor

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A Study of the Physical Experience Using Serious Game Design Traffic Safety Education for Children applied using 3D Depth Gesture Recognition Technology (3차원 동작인식기술을 적용한 어린이 교통안전교육 체감형 기능성 게임디자인 연구)

  • Jang, Chang-Ik
    • Journal of Korea Game Society
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    • v.12 no.6
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    • pp.5-14
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    • 2012
  • The purpose of this paper is to demonstrate how three-dimensional gesture recognition technology, in children's traffic safety programs, can be an effective solution for instructing children in the safest ways to interact with traffic. In terms of traffic accidents, walking unaccompanied is the most dangerous traffic related activity for children. By using a three-dimensional serous game training program that implements gesture recognition, more accurate real life scenarios can be implemented in existing children's traffic training programs. The implementation of this technology will increase the possibility of changing the habits and attitudes of children, which in turn will lower the amount of walking related traffic accidents in children.

Motion Control of a Mobile Robot Using Natural Hand Gesture (자연스런 손동작을 이용한 모바일 로봇의 동작제어)

  • Kim, A-Ram;Rhee, Sang-Yong
    • Journal of the Korean Institute of Intelligent Systems
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    • v.24 no.1
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    • pp.64-70
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    • 2014
  • In this paper, we propose a method that gives motion command to a mobile robot to recognize human being's hand gesture. Former way of the robot-controlling system with the movement of hand used several kinds of pre-arranged gesture, therefore the ordering motion was unnatural. Also it forced people to study the pre-arranged gesture, making it more inconvenient. To solve this problem, there are many researches going on trying to figure out another way to make the machine to recognize the movement of the hand. In this paper, we used third-dimensional camera to obtain the color and depth data, which can be used to search the human hand and recognize its movement based on it. We used HMM method to make the proposed system to perceive the movement, then the observed data transfers to the robot making it to move at the direction where we want it to be.

Recognition of Natural Hand Gesture by Using HMM (HMM을 이용한 자연스러운 손동작 인식)

  • Kim, A-Ram;Rhee, Sang-Yong
    • Journal of the Korean Institute of Intelligent Systems
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    • v.22 no.5
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    • pp.639-645
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    • 2012
  • In this paper, we propose a method that gives motion command to a mobile robot to recognize human being's hand gesture. Former way of the robot-controlling system with the movement of hand used several kinds of pre-arranged gesture, therefore the ordering motion was unnatural. Also it forced people to study the pre-arranged gesture, making it more inconvenient. To solve this problem, there are many researches going on trying to figure out another way to make the machine to recognize the movement of the hand. In this paper, we used third-dimensional camera to obtain the color and depth data, which can be used to search the human hand and recognize its movement based on it. We used HMM method to make the proposed system to perceive the movement, then the observed data transfers to the robot making it to move at the direction where we want it to be.

An Extraction Method of Meaningful Hand Gesture for a Robot Control (로봇 제어를 위한 의미 있는 손동작 추출 방법)

  • Kim, Aram;Rhee, Sang-Yong
    • Journal of the Korean Institute of Intelligent Systems
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    • v.27 no.2
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    • pp.126-131
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    • 2017
  • In this paper, we propose a method to extract meaningful motion among various kinds of hand gestures on giving commands to robots using hand gestures. On giving a command to the robot, the hand gestures of people can be divided into a preparation one, a main one, and a finishing one. The main motion is a meaningful one for transmitting a command to the robot in this process, and the other operation is a meaningless auxiliary operation to do the main motion. Therefore, it is necessary to extract only the main motion from the continuous hand gestures. In addition, people can move their hands unconsciously. These actions must also be judged by the robot with meaningless ones. In this study, we extract human skeleton data from a depth image obtained by using a Kinect v2 sensor and extract location data of hands data from them. By using the Kalman filter, we track the location of the hand and distinguish whether hand motion is meaningful or meaningless to recognize the hand gesture by using the hidden markov model.

ILOCAT: an Interactive GUI Toolkit to Acquire 3D Positions for Indoor Location Based Services (ILOCAT: 실내 위치 기반 서비스를 위한 3차원 위치 획득 인터랙티브 GUI Toolkit)

  • Kim, Seokhwan
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.7
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    • pp.866-872
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    • 2020
  • Indoor location-based services provide a service based on the distance between an object and a person. Recently, indoor location-based services are often implemented using inexpensive depth sensors such as Kinect. The depth sensor provides a function to measure the position of a person, but the position of an object must be acquired manually using a tool. To acquire a 3D position of an object, it requires 3D interaction, which is difficult to a general user. GUI(Graphical User Interface) is relatively easy to a general user but it is hard to gather a 3D position. This study proposes the Interactive LOcation Context Authoring Toolkit(ILOCAT), which enables a general user to easily acquire a 3D position of an object in real space using GUI. This paper describes the interaction design and implementation of ILOCAT.

Investigation for Shoulder Kinematics Using Depth Sensor-Based Motion Analysis System (깊이 센서 기반 모션 분석 시스템을 사용한 어깨 운동학 조사)

  • Lee, Ingyu;Park, Jai Hyung;Son, Dong-Wook;Cho, Yongun;Ha, Sang Hoon;Kim, Eugene
    • Journal of the Korean Orthopaedic Association
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    • v.56 no.1
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    • pp.68-75
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    • 2021
  • Purpose: The purpose of this study was to analyze the motion of the shoulder joint dynamically through a depth sensor-based motion analysis system for the normal group and patients group with shoulder disease and to report the results along with a review of the relevant literature. Materials and Methods: Seventy subjects participated in the study and were categorized as follows: 30 subjects in the normal group and 40 subjects in the group of patients with shoulder disease. The patients with shoulder disease were subdivided into the following four disease groups: adhesive capsulitis, impingement syndrome, rotator cuff tear, and cuff tear arthropathy. Repeating abduction and adduction three times, the angle over time was measured using a depth sensor-based motion analysis system. The maximum abduction angle (θmax), the maximum abduction angular velocity (ωmax), the maximum adduction angular velocity (ωmin), and the abduction/adduction time ratio (tabd/tadd) were calculated. The above parameters in the 30 subjects in the normal group and 40 subjects in the patients group were compared. In addition, the 30 subjects in the normal group and each subgroup (10 patients each) according to the four disease groups, giving a total of five groups, were compared. Results: Compared to the normal group, the maximum abduction angle (θmax), the maximum abduction angular velocity (ωmax), and the maximum adduction angular velocity (ωmin) were lower, and abduction/adduction time ratio (tabd/tadd) was higher in the patients with shoulder disease. A comparison of the subdivided disease groups revealed a lower maximum abduction angle (θmax) and the maximum abduction angular velocity (ωmax) in the adhesive capsulitis and cuff tear arthropathy groups than the normal group. In addition, the abduction/adduction time ratio (tabd/tadd) was higher in the adhesive capsulitis group, rotator cuff tear group, and cuff tear arthropathy group than in the normal group. Conclusion: Through an evaluation of the shoulder joint using the depth sensor-based motion analysis system, it was possible to measure the range of motion, and the dynamic motion parameter, such as angular velocity. These results show that accurate evaluations of the function of the shoulder joint and an in-depth understanding of shoulder diseases are possible.

Augmented Reality Authoring Tool with Marker & Gesture Interactive Features (마커 및 제스처 상호작용이 가능한 증강현실 저작도구)

  • Shim, Jinwook;Kong, Minje;Kim, Hayoung;Chae, Seungho;Jeong, Kyungho;Seo, Jonghoon;Han, Tack-Don
    • Journal of Korea Multimedia Society
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    • v.16 no.6
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    • pp.720-734
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    • 2013
  • In this paper, we suggest an augmented reality authoring tool system that users can easily make augmented reality contents using hand gesture and marker-based interaction methods. The previous augmented reality authoring tools are focused on augmenting a virtual object and to interact with this kind of augmented reality contents, user used the method utilizing marker or sensor. We want to solve this limited interaction method problem by applying marker based interaction method and gesture interaction method using depth sensing camera, Kinect. In this suggested system, user can easily develop simple form of marker based augmented reality contents through interface. Also, not just providing fragmentary contents, this system provides methods that user can actively interact with augmented reality contents. This research provides two interaction methods, one is marker based method using two markers and the other is utilizing marker occlusion. In addition, by recognizing and tracking user's bare hand, this system provides gesture interaction method which can zoom-in, zoom-out, move and rotate object. From heuristic evaluation about authoring tool and compared usability about marker and gesture interaction, this study confirmed a positive result.