Three-dimensional Motion Skeleton Reconstruction Algorithm for Gymnastic Dancing Movements

Aiming at the problem of inaccurate matching results in the traditional three-dimensional reconstruction algorithm of gymnastic skeleton, a three-dimensional motion skeleton reconstruction algorithm of gymnastic dance action is proposed. Taking the center of gravity of the human body as the origin, the position of other nodes in the camera coordinate system relative to the center point of the human skeleton model is calculated, and the human skeleton data collection is completed through action division and posture feature calculation. Polynomial density is introduced into the integration of convolution surface, and the human body model of convolution surface is established according to convolution surface. By using the method of binary parameter matching, the accuracy of the matching results is improved, and the three-dimensional skeleton of gymnastic dance movement is reconstructed. The experimental results show that the fitting degree between the proposed method and the actual reconstruction result is 99.8%, and the reconstruction result of this algorithm has high accuracy.

Pedestrian motion centroid model based on robot dynamics

In recent years, with the rapid development of computer vision technology, image-based human body research has become an important task, such as pedestrian target detection, trajectory tracking, posture estimation and behaviour recognition. The centre of mass is one of the important characteristics that can reflect the phenomenon of pedestrian movement. This paper first introduces the biped robot model in robotics, starting from forward and inverse kinematics, to find the mapping relationship between the position of each joint and the pose of the end effector. Then, corresponding to the skeleton model of the human joint points, the characteristics of the bone posture and joint angle are determined. The moment of inertia factor is introduced, and the motion superposition of different joint points is considered to establish a pedestrian motion centroid model. By calculating the equivalent dynamic centroid, the pedestrian kinematics law can be explored and the pedestrian movement mechanism can be more deeply recognized.

Improved 3D Human Motion Capture Using Kinect Skeleton and Depth Sensor

Kinect has been utilized as a cost-effective, easy-to-use motion capture sensor using the Kinect skeleton algorithm. However, a limited number of landmarks and inaccuracies in tracking the landmarks’ positions restrict Kinect’s capability. In order to increase the accuracy of motion capturing using Kinect, joint use of the Kinect skeleton algorithm and Kinect-based marker tracking was applied to track the 3D coordinates of multiple landmarks on human. The motion’s kinematic parameters were calculated using the landmarks’ positions by applying the joint constraints and inverse kinematics techniques. The accuracy of the proposed method and OptiTrack (NaturalPoint, Inc., USA) was evaluated in capturing the joint angles of a humanoid (as ground truth) in a walking test. In order to evaluate the accuracy of the proposed method in capturing the kinematic parameters of a human, lower body joint angles of five healthy subjects were extracted using a Kinect, and the results were compared to Perception Neuron (Noitom Ltd., China) and OptiTrack data during ten gait trials. The absolute agreement and consistency between each optical system and the robot data in the robot test and between each motion capture system and OptiTrack data in the human gait test were determined using intraclass correlations coefficients (ICC3). The reproducibility between systems was evaluated using Lin’s concordance correlation coefficient (CCC). The correlation coefficients with 95% confidence intervals (95%CI) were interpreted substantial for both OptiTrack and proposed method (ICC > 0.75 and CCC > 0.95) in humanoid test. The results of the human gait experiments demonstrated the advantage of the proposed method (ICC > 0.75 and RMSE = 1.1460°) over the Kinect skeleton model (ICC < 0.4 and RMSE = 6.5843°).

Biomechanism and exercise effect of fitness walking using twin walking sticks

In Japan, walking poles with pairs of sticks developed exclusively for fitness walking have been designed. A new concept of walking style (WS) has been conceived using these walking sticks to “effectively” walk around the city, comprehensive sports parks, or at rehabilitation hospitals. Stick manufacturers are promoting its health benefits; however, evidence supporting these claims is lacking. Hence, this study aimed to measure the influence of walking sticks and evaluate the exercise effect based on functional physical fitness related to WS characteristics. The participants were 12 WS instructors. They engaged in WS at a comfortable speed after walking normally at the same speed (WN) for ∼5 m (seven times), followed by WS again. The walking speed, step length, stride width, walk ratio, one-leg support time, and trajectory of the center of gravity (CG) (in the horizontal and vertical directions of one walking cycle) calculated from the whole-body skeleton model were analyzed. The gait of WS increased the step length, step width, and walking ratio as compared with that of WN (p&lt;0.05). WS likely reduce cadence and one-leg support time (p&lt;0.05). The CG locus in the left-right direction showed no significant differences between WS and WN. The maximum value of the CG locus in the vertical direction was high in WS (p&lt;0.05). WS can be used as a navigation training tool that improves a walker's exercise efficiency and left-right leg coordination, thereby improving walking posture. This may help reduce the anxiety due to injuries and pain that may occur while walking.

Application of Virtual Reality Human-Computer Interaction Technology Based on the Sensor in English Teaching

In order to improve the online English teaching effect, the paper applies the sensor and human-computer interaction into the English teaching. The paper improves the sensor information by applying Kalman Filter, combines sensor positioning algorithm to trace the students in the English teaching online, and turns the kernels by the skeleton algorithm into corresponding coordinates of space rectangular coordinate system taking the waist as a coordinate origin to get a human-computer interaction skeleton model in the virtual reality. According to the actual needs of English teaching human-computer interaction, the paper builds a new English teaching system based on the sensor and the human-computer interaction and tests its performance. The experiments suggest that the smart system in the paper can effectively improve English teaching effects.

Research on Action Recognition Method of Dance Video Image Based on Human-Computer Interaction

Human-computer interaction technology simplifies the complicated procedures, which aims at solving the problems of inadequate description and low recognition rate of dance action, studying the action recognition method of dance video image based on human-computer interaction. This method constructs the recognition process based on human-computer interaction technology, constructs the human skeleton model according to the spatial position of skeleton, motion characteristics of skeleton, and change angles of skeleton, describes the dance posture features by generating skeleton node graph, and extracts the key frames of dance video image by using the clustering algorithm to recognize the dance action. The experimental results show that the recognition rate of this method under different entropy values is not less than 88%. Under the test conditions of complex, dark, bright, and multiuser interference, this method can make the model to describe the dance posture accurately. Furthermore, the average recognition rates are 93.43%, 91.27%, 97.15%, and 89.99%, respectively. It is suitable for action recognition of most dance video images.

Aircraft System State Recognition and Fault Prediction Based on a Test Diagnostic Model

The existing testability models for fault prognosis of aircraft systems limit the implementation of prognosis and health management systems. This paper develops a test diagnosis modeling method and relevant algorithms to support dynamic testing and to evaluate fault prognostic ability during aircraft system design. According to the system principles and the complex function structure of aircraft systems, a test diagnostic model is established by integrating testing and prognostic information with a test diagnostic skeleton model using multi-signal flow. New test indexes are identified to assess the testability and prognostic ability of aircraft systems. Relevant state recognition and fault prediction algorithms are established by fusing the improved particle swarm optimization algorithm and Hidden Semi-Markov Model. The feasibility and validity of the test diagnostic modeling method and relevant algorithms are verified in an aircraft’s engine bleed air system. Training and test show that the model can support analysis and estimation, and the algorithms can ensure accurate results after training the HSMM using improved PSO algorithm.

Experimental and Numerical Simulation of Neuro Fuzzy Based Cartesian Robot for Soft Material Cutting

Present technology used for soft material cutting robot are laser, water-jet, ultrasonic, plasma and oxy-gas cutting. The scope for designing and fabrication of soft material cutting robots are increasing due to its cost effectiveness and quality of cutting. Cartesian robots are mainly used in assembly and manufacturing applications. They also have a high degree of mechanical rigidity, accuracy, and repeatability. A previous work of more elementary kind was used as a skeleton model to start this work The purpose of the work is the maintenance and implementation of a 4 Degree of freedom robot and also to provide intelligence to the robot using Fuzzy logic and Neuro-Fuzzy for soft material cutting. The kinematic modeling of robot manipulator is done using Denavit-Hartenberg (D-H) parameterization method and Euler-Lagrange method is used for dynamic analysis to determine actuator torque for each joint. The image is acquired with the help of the digital camera which is fixed in a suitable position so that it can scan the entire workspace. Prewitt edge detection algorithm was used for image processing and analysis. The signal for the cutting is interfaced through the Arduino Uno r3 controller.

Stochastic parametric skeletal dosimetry model for humans: General approach and application to active marrow exposure from bone-seeking beta-particle emitters

The objective of this study is to develop a skeleton model for assessing active marrow dose from bone-seeking beta-emitting radionuclides. This article explains the modeling methodology which accounts for individual variability of the macro- and microstructure of bone tissue. Bone sites with active hematopoiesis are assessed by dividing them into small segments described by simple geometric shapes. Spongiosa, which fills the segments, is modeled as an isotropic three-dimensional grid (framework) of rod-like trabeculae that “run through” the bone marrow. Randomized multiple framework deformations are simulated by changing the positions of the grid nodes and the thickness of the rods. Model grid parameters are selected in accordance with the parameters of spongiosa microstructures taken from the published papers. Stochastic modeling of radiation transport in heterogeneous media simulating the distribution of bone tissue and marrow in each of the segments is performed by Monte Carlo methods. Model output for the human femur at different ages is provided as an example. The uncertainty of dosimetric characteristics associated with individual variability of bone structure was evaluated. An advantage of this methodology for the calculation of doses absorbed in the marrow from bone-seeking radionuclides is that it does not require additional studies of autopsy material. The biokinetic model results will be used in the future to calculate individual doses to members of a cohort exposed to 89,90Sr from liquid radioactive waste discharged to the Techa River by the Mayak Production Association in 1949–1956. Further study of these unique cohorts provides an opportunity to gain more in-depth knowledge about the effects of chronic radiation on the hematopoietic system. In addition, the proposed model can be used to assess the doses to active marrow under any other scenarios of 90Sr and 89Sr intake to humans.