论文信息 - Arm Orientation Estimation Method with Multiple Devices for NUI/NUX

Arm Orientation Estimation Method with Multiple Devices for NUI/NUX

Motion estimation is a key Natural User Interface/Natural User Experience (NUI/NUX) technology to utilize motions as commands. HTC VIVE is an excellent device for estimating motions but only considers the positions of hands, not the orientations of arms. Even if the positions of the hands are the same, the meaning of motions can differ according to the orientations of the arms. Therefore, when the positions of arms are measured and utilized, their orientations should be estimated as well. This paper proposes a method for estimating the arm orientations based on the Bayesian probability of the hand positions measured in advance. In experiments, the proposed method was used to measure the hand positions with HTC VIVE. The results showed that the proposed method estimated orientations with an error rate of about 19%, but the possibility of estimating the orientation of any body part without additional devices was demonstrated.

[1] IlJu Ko,et al. A climbing motion recognition method using anatomical information for screen climbing games , 2017, Human-centric Computing and Information Sciences.

[2] Xu Xu,et al. A computer vision based method for 3D posture estimation of symmetrical lifting. , 2018, Journal of biomechanics.

[3] Jong Hyuk Park,et al. Bayesian Probability-Based Motion Estimation Method in Ubiquitous Computing Environments , 2015, CSA/CUTE.

[4] Yunhui Liu,et al. Vision-Based Calibration of Dual RCM-Based Robot Arms in Human-Robot Collaborative Minimally Invasive Surgery , 2018, IEEE Robotics and Automation Letters.

[5] Kyoungsu Oh,et al. Interactive Experience Room Using Infrared Sensors and User's Poses , 2017, J. Inf. Process. Syst..

[6] Kyungeun Cho,et al. Genetic Algorithm-Based Motion Estimation Method using Orientations and EMGs for Robot Controls , 2018, Sensors.

[7] Weiqiang Zhang,et al. Genetic algorithm-based adaptive weight decision method for motion estimation framework , 2018, The Journal of Supercomputing.

[8] Jong Hyuk Park,et al. Motion estimation framework and authoring tools based on MYOs and Bayesian probability , 2016, Multimedia Tools and Applications.

[9] Simon Fong,et al. A 3D localisation method in indoor environments for virtual reality applications , 2017, Human-centric Computing and Information Sciences.