Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6

kinect Related Publications

6 MAGNI Dynamics: A Vision-Based Kinematic and Dynamic Upper-Limb Model for Intelligent Robotic Rehabilitation

Authors: Alexandros Lioulemes, Michail Theofanidis, Varun Kanal, Konstantinos Tsiakas, Maher Abujelala, Chris Collander, William B. Townsend, Angie Boisselle, Fillia Makedon

Abstract:

This paper presents a home-based robot-rehabilitation instrument, called ”MAGNI Dynamics”, that utilized a vision-based kinematic/dynamic module and an adaptive haptic feedback controller. The system is expected to provide personalized rehabilitation by adjusting its resistive and supportive behavior according to a fuzzy intelligence controller that acts as an inference system, which correlates the user’s performance to different stiffness factors. The vision module uses the Kinect’s skeletal tracking to monitor the user’s effort in an unobtrusive and safe way, by estimating the torque that affects the user’s arm. The system’s torque estimations are justified by capturing electromyographic data from primitive hand motions (Shoulder Abduction and Shoulder Forward Flexion). Moreover, we present and analyze how the Barrett WAM generates a force-field with a haptic controller to support or challenge the users. Experiments show that by shifting the proportional value, that corresponds to different stiffness factors of the haptic path, can potentially help the user to improve his/her motor skills. Finally, potential areas for future research are discussed, that address how a rehabilitation robotic framework may include multisensing data, to improve the user’s recovery process.

Keywords: Dynamics, Kinematics, rehabilitation robotics, Human-Robot Interaction, kinect, haptic control, artificial intelligence

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5 Stereotypical Motor Movement Recognition Using Microsoft Kinect with Artificial Neural Network

Authors: M. Jazouli, S. Elhoufi, A. Majda, A. Zarghili, R. Aalouane

Abstract:

Autism spectrum disorder is a complex developmental disability. It is defined by a certain set of behaviors. Persons with Autism Spectrum Disorders (ASD) frequently engage in stereotyped and repetitive motor movements. The objective of this article is to propose a method to automatically detect this unusual behavior. Our study provides a clinical tool which facilitates for doctors the diagnosis of ASD. We focus on automatic identification of five repetitive gestures among autistic children in real time: body rocking, hand flapping, fingers flapping, hand on the face and hands behind back. In this paper, we present a gesture recognition system for children with autism, which consists of three modules: model-based movement tracking, feature extraction, and gesture recognition using artificial neural network (ANN). The first one uses the Microsoft Kinect sensor, the second one chooses points of interest from the 3D skeleton to characterize the gestures, and the last one proposes a neural connectionist model to perform the supervised classification of data. The experimental results show that our system can achieve above 93.3% recognition rate.

Keywords: ASD, Artificial Neural Network, kinect, stereotypical motor movements, repetitive gesture

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4 Laban Movement Analysis Using Kinect

Authors: Ran Bernstein, Tal Shafir, Rachelle Tsachor, Karen Studd, Assaf Schuster

Abstract:

Laban Movement Analysis (LMA), developed in the dance community over the past seventy years, is an effective method for observing, describing, notating, and interpreting human movement to enhance communication and expression in everyday and professional life. Many applications that use motion capture data might be significantly leveraged if the Laban qualities will be recognized automatically. This paper presents an automated recognition method of Laban qualities from motion capture skeletal recordings and it is demonstrated on the output of Microsoft’s Kinect V2 sensor.

Keywords: kinect, Laban movement analysis, Machine Learning

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3 Interactive Shadow Play Animation System

Authors: Bo Wan, Xiu Wen, Lingling An, Xiaoling Ding

Abstract:

The paper describes a Chinese shadow play animation system based on Kinect. Users, without any professional training, can personally manipulate the shadow characters to finish a shadow play performance by their body actions and get a shadow play video through giving the record command to our system if they want. In our system, Kinect is responsible for capturing human movement and voice commands data. Gesture recognition module is used to control the change of the shadow play scenes. After packaging the data from Kinect and the recognition result from gesture recognition module, VRPN transmits them to the server-side. At last, the server-side uses the information to control the motion of shadow characters and video recording. This system not only achieves human-computer interaction, but also realizes the interaction between people. It brings an entertaining experience to users and easy to operate for all ages. Even more important is that the application background of Chinese shadow play embodies the protection of the art of shadow play animation.

Keywords: Gesture Recognition, kinect, VRPN, shadow play animation

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2 Capture and Feedback in Flying Disc Throw with use of Kinect

Authors: Takeshi Shima, Yasuhisa Tamura, Koji Yamaoka, Masataka Uehara

Abstract:

This paper proposes a three-dimensional motion capture and feedback system of flying disc throwing action learners with use of Kinect device. Rather than conventional 3-D motion capture system, Kinect has advantages of cost merit, easy system development and operation. A novice learner of flying disc is trained to keep arm movement in steady height, to twist the waist, and to stretch the elbow according to the waist angle. The proposing system captures learners- body movement, checks their skeleton positions in pre-motion / motion / post-motion in several ways, and displays feedback messages to refine their actions.

Keywords: Feedback, kinect, capture, Flying disc, throwing movement

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1 Augmented Reality Interaction System in 3D Environment

Authors: HernSoo Hahn, Youngjoon Han, Sunhyoung Lee, Askar Akshabayev, Beisenbek Baisakov

Abstract:

It is important to give input information without other device in AR system. One solution is using hand for augmented reality application. Many researchers have proposed different solutions for hand interface in augmented reality. Analyze Histogram and connecting factor is can be example for that. Various Direction searching is one of robust way to recognition hand but it takes too much calculating time. And background should be distinguished with skin color. This paper proposes a hand tracking method to control the 3D object in augmented reality using depth device and skin color. Also in this work discussed relationship between several markers, which is based on relationship between camera and marker. One marker used for displaying virtual object and three markers for detecting hand gesture and manipulating the virtual object.

Keywords: Augmented Reality, kinect, marker, hand recognition, depth map, YCbCr color model

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