Quantitative analysis of the morphing wing mechanism of raptors:IMMU-based motion capture system and its application on gestures of a Falco peregrinus

This paper presented a novel tinny motion capture system for measuring bird posture based on inertial and magnetic measurement units that are made up of micromachined gyroscopes, accelerometers, and magnetometers. Multiple quaternion-based extended Kalman filters were implemented to estimate the absolute orientations to achieve high accuracy.Under the guidance of ornithology experts, the extending/contracting motions and flapping cycles were recorded using the developed motion capture system, and the orientation of each bone was also analyzed. The captured flapping gesture of the Falco peregrinus is crucial to the motion database of raptors as well as the bionic design.

Kinematic calibration under the expectation maximization framework for exoskeletal inertial motion capture system

This study presents a kinematic calibration method for exoskeletal inertial motion capture (EI-MoCap) system with considering the random colored noise such as gyroscopic drift.In this method, the geometric parameters are calibrated by the traditional calibration method at first. Then, in order to calibrate the parameters affected by the random colored noise, the expectation maximization (EM) algorithm is introduced. Through the use of geometric parameters calibrated by the traditional calibration method, the iterations under the EM framework are decreased and the efficiency of the proposed method on embedded system is improved. The performance of the proposed kinematic calibration method is compared to the traditional calibration method. Furthermore, the feasibility of the proposed method is verified on the EI-MoCap system. The simulation and experiment demonstrate that the motion capture precision is significantly improved by 16.79%and 7.16%respectively in comparison to the traditional calibration method.

Review of techniques for motion capture data processing

In order to high reality and efficiency, the technique computer animation. With the development of motion capture, a of motion capture （MoCap） has been widely used in the field of large amount of motion capture databases are available and this is significant for the reuse of motion data. But due to the high degree of freedoms and high capture frequency, the dimension of the mo- tion capture data is usually very high and this will lead to a low efficiency in data processing. So how to process the high dimension data and design an efficient and effective retrieval approach has become a challenge which we can＇t ignore. In this paper, first we lay out some problems about the key techniques in motion capture data processing. Then the existing approaches are analyzed and sum- marized. At last, some future work is proposed.

Fast Individual Facial Animation Framework Based on Motion Capture Data

Based upon motion capture,a semi-automatic technique for fast facial animation was implemented. While capturing the facial expressions from a performer,a camera was used to record her /his front face as a texture map. The radial basis function( RBF) technique was utilized to deform a generic facial model and the texture was remapped to generate a personalized face.Partitioning the personalized face into three regions and using the captured facial expression data,the RBF and Laplacian operator,and mean-value coordinates were implemented to deform each region respectively. With shape blending,the three regions were combined together to construct the final face model. Our results show that the technique is efficient in generating realistic facial animation.

Motion Capture for Puppet Control Using Integrated Sensor System

The paper aims to execute puppet without restrictions by controling puppet using robot. We controling puppet in the same way as the present puppet, but we perform this by robot. It offers more advantages and lessen the weak points. It needs various actions and expressions because of the nature of a puppet. The biggest problem which executes this is the ways to create a system. This thesis proposes motion capture of developed method with solution of this problem. So, we create various contents needed by puppet. In this part, developed method means a mixed method on the basis of optical system and magnetic system used mainly for the present method of motion capture. We lessen the weak points of each method and propoe solution of create motion for pupct by offering more advantages. So we solve difficulties of executing puppet and probable probkans when we execute puppet by using robot. The solution of this thesis is proven by applying control of puppet.

Application of Optical Motion Capture Technology in Power Safety Entitative Simulation Training System

The safety production is critical to stable development of Chinese electric power industry. With the development of electric power enterprises, the requirements of its employees are also becoming higher and higher. In this paper, an optical motion capture system based on the virtual reality technology is proposed to meet the requirements of the power enterprise for the qualified business ability. Electric power equipment, power equipment model entitative operating environment and the human model are established by electric power simulation unit, ZigBee technology and OpenGL graphics library. The problem of missing feature points is solved by applying the human model driven algorithm and the Kalman filtering algorithm. The experimental results show that it is more accurate to use Kalman filtering algorithm to extract the feature point in tracking process of actual motion capture and real-time animation display. The average absolute error of 3D coordinates is 1.61 mm and the average relative error is 2.23%. The system can improve trainees’ sense of experience and immersion.

Automatic Key-Frame Extraction from Optical Motion Capture Data

Optical motion capture is an increasingly popular animation technique. In the last few years, plenty of methods have been proposed for key-frame extraction of motion capture data, and it is a common method to extract key-frame using quaternion. Here, one main difficulty is due to the fact that previous algorithms often need to manually set various parameters. In addition, it is problematic to predefine the appropriate threshold without knowing the data content. In this paper, we present a novel adaptive threshold-based extraction method. Key-frame can be found according to quaternion distance. We propose a simple and efficient algorithm to extract key-frame from a motion sequence based on adaptive threshold. It is convenient with no need to predefine parameters to meet certain compression ratio. Experimental results of many motion captures with different traits demonstrate good performance of the proposed algorithm. Our experiments show that one can typically cut down the process of extraction from several minutes to a couple of seconds.

Silk road dance exhibition system based on motion capture

Silk Road dance is an excellent traditional Chinese dance drama, which has high artistic values. This article introduces the virtual performance techniques of Silk Road based on motion capture. First, obtain the dance data using motion capture technique according to the features of dance itself, then establish figure model, finally combines these data to make 3-D animation system to perform Silk Road, meanwhile designs some interfaces to introduce it. This system excavates details of the dance, and can be reference of man-machine interaction and animation production.

Natural human–computer interaction control of multi operators in collaborative virtual maintenance based on optical human motion capture system

Aiming at the human–computer interaction control(HCIC)requirements of multi operators in collaborative virtual maintenance(CVM),real-time motion capture and simulation drive of multi operators with optical human motion capture system(HMCS)is proposed.The detailed realization process of real-time motion capture and data drive for virtual operators in CVM environment is presented to actualize the natural and online interactive operations.In order to ensure the cooperative and orderly interactions of virtual operators with the input operations of actual operators,collaborative HCIC model is established according to specific planning,allocating and decision-making of different maintenance tasks as well as the human–computer interaction features and collaborative maintenance operation features among multi maintenance trainees in CVM process.Finally,results of the experimental implementation validate the effectiveness and practicability of proposed methods,models,strategies and mechanisms.

Markerless human motion capture by Markov random field and dynamic graph cuts with color constraints

Currently, many vision-based motion capture systems require passive markers attached to key loca- tions on the human body. However, such systems are intrusive with limited application. The algorithm that we use for human motion capture in this paper is based on Markov random field （MRF） and dynamic graph cuts. It takes full account of the impact of 3D reconstruction error and integrates human motion capture and 3D reconstruction into MRF-MAP framework. For more accurate and robust performance, we extend our algorithm by incorporating color constraints into the pose estimation process. The advantages of incorporating color constraints are demonstrated by experimental results on several video sequences.

3D hypothesis clustering for cross-view matching in multiperson motion capture

We present a multiview method for markerless motion capture of multiple people. The main challenge in this problem is to determine crossview correspondences for the 2 D joints in the presence of noise. We propose a 3 D hypothesis clustering technique to solve this problem. The core idea is to transform joint matching in 2 D space into a clustering problem in a 3 D hypothesis space. In this way, evidence from photometric appearance, multiview geometry, and bone length can be integrated to solve the clustering problem efficiently and robustly. Each cluster encodes a set of matched 2 D joints for the same person across different views, from which the 3 D joints can be effectively inferred. We then assemble the inferred 3 D joints to form full-body skeletons for all persons in a bottom–up way. Our experiments demonstrate the robustness of our approach even in challenging cases with heavy occlusion,closely interacting people, and few cameras. We have evaluated our method on many datasets, and our results show that it has significantly lower estimation errors than many state-of-the-art methods.

PESTA: An Elastic Motion Capture Data Retrieval Method

Prevalent use of motion capture(MoCap)produces large volumes of data and MoCap data retrieval becomes crucial for efficient data reuse.MoCap clips may not be neatly segmented and labeled,increasing the difficulty of retrieval.In order to effectively retrieve such data,we propose an elastic content-based retrieval scheme via unsupervised posture encoding and strided temporal alignment(PESTA)in this work.It retrieves similarities at the sub-sequence level,achieves robustness against singular frames and enables control of tradeoff between precision and efficiency.It firstly learns a dictionary of encoded postures utilizing unsupervised adversarial autoencoder techniques and,based on which,compactly symbolizes any MoCap sequence.Secondly,it conducts strided temporal alignment to align a query sequence to repository sequences to retrieve the best-matching sub-sequences from the repository.Further,it extends to find matches for multiple sub-queries in a long query at sharply promoted efficiency and minutely sacrificed precision.Outstanding performance of the proposed scheme is well demonstrated by experiments on two public MoCap datasets and one MoCap dataset captured by ourselves.

A physics-based approach to motion capture data processing for virtual plant modeling and simulation

Dynamic virtual plant simulation is an attractive research issue in both botany and computer graphics.Data-driven method is an efficient way for motion analysis and animation synthesis.As a widely used tool,motion capture has been used in plant motion data acquisition and analysis.The most prominent and important problem in motion capture for plants is primary data processing such as missing markers reconstruction.This paper presents a novel physics-based approach to motion capture data processing of plants.Firstly,a physics-based mechanics model is found by Lagrangian mechanics for a motion captured plant organ such as a leaf,and then its dynamic mechanical properties are analyzed and relevant model parameters are evaluated.Further,by using the physical model with evaluated parameters,we can calculate the next positions of a maker to reconstruct the missing makers in motion capture sequence.We take an example of a maize leaf and pachira leaf to examine the proposed approach,and the results show that the physics-based method is feasible and effective for plant motion data processing.

Data compensation based on the additional feature information for collaborative interactive operation with optical human motion capture system

As the effective capture region of optical motion capture system is limited by quantity,installation mode,resolution and focus of infrared cameras,the reflective markers on certain body parts(such as wrists,elbows,etc.)of multi-actual trainees may be obscured when they perform the collaborative interactive operation.To address this issue,motion data compensation method based on the additional feature information provided by the electromagnetic spatial position tracking equipment is proposed in this paper.The main working principle and detailed realization process of the proposed method are introduced step by step,and the practical implementation is presented to illustrate its validity and efficiency.The results show that the missing capture data and motion information of relevant obscured markers on arms can be retrieved with the proposed method,which can avoid the simulation motions of corresponding virtual operators being interrupted and deformed during the collaborative interactive operation process performed by multiactual trainees with optical human motion capture system in a limited capture range.

IMU-based motion capture system for rehabilitation applications: A systematic review

In recent years,the use of inertial measurement unit(IMU)-based motion capture(Mocap)systems in rehabilitation has grown significantly.This paper aimed to provide an overview of current IMUbased Mocap system designs in the field of rehabilitation,explore the specific applications and implementation of these systems,and discuss potential future developments considering sensor limitations.For this review,a systematic literature search was conducted using Scopus,IEEE Xplore,PubMed,and Web of Science from 2013 to 2022.A total of 65 studies were included and analyzed based on their rehabilitation application,target population,and system deployment and measurement.The proportion of rehabilitation assessment,training,and both were 82%,12%,and 6%respectively.The results showed that primary focus of the studies was stroke that was one of the most commonly studied pathological disease.Additionally,general rehabilitation without targeting a specific pathology was also examined widely,with a particular emphasis on gait analysis.The most common sensor configuration for gait analysis was two IMUs measuring spatiotemporal parameters of the lower limb.However,the lack of training applications and upper limb studies could be attributed to the limited battery life and sensor drift.To address this issue,the use of low-power chips and low-consumption transmission pathways was a potential way to extend usage time for long-term training.Furthermore,we suggest the development of a highly integrated multi-modal system with sensor fusion.

Differences between lower extremity joint running kinetics captured by marker-based and markerless systems were speed dependent

Background:The development of computer vision technology has enabled the use of markerless movement tracking for biomechanical analysis.Recent research has reported the feasibility of markerless systems in motion analysis but has yet to fully explore their utility for capturing faster movements,such as running.Applied studies using markerless systems in clinical and sports settings are still lacking.Thus,the present study compared running biomechanics estimated by marker-based and markerless systems.Given running speed not only affects sports performance but is also associated with clinical injury prevention,diagnosis,and rehabilitation,we aimed to investigate the effects of speed on the comparison of estimated lower extremity joint moments and powers between markerless and marker-based technologies during treadmill running as a concurrent validating study.Methods:Kinematic data from marker-based/markerless technologies were collected,along with ground reaction force data,from 16 young adults running on an instrumented treadmill at 3 speeds:2.24 m/s,2.91 m/s,and 3.58 m/s(5.0 miles/h,6.5 miles/h,and 8.0 miles/h).Sagittal plane moments and powers of the hip,knee,and ankle were calculated by inverse dynamic methods.Time series analysis and statistical parametric mapping were used to determine system differences.Results:Compared to the marker-based system,the markerless system estimated increased lower extremity joint kinetics with faster speed during the swing phase in most cases.Conclusion:Despite the promising application of markerless technology in clinical settings,systematic markerless overestimation requires focused attention.Based on segment pose estimations,the centers of mass estimated by markerless technologies were farther away from the relevant distal joint centers,which led to greater joint moments and powers estimates by markerless vs.marker-based systems.The differences were amplified by running speed.

Technological advancements in the analysis of human motion and posture management through digital devices

Technological development of motion and posture analyses is rapidly progressing,especially in rehabilitation settings and sport biomechanics.Consequently,clear discrimination among different measurement systems is required to diversify their use as needed.This review aims to resume the currently used motion and posture analysis systems,clarify and suggest the appropriate approaches suitable for specific cases or contexts.The currently gold standard systems of motion analysis,widely used in clinical settings,present several limitations related to marker placement or long procedure time.Fully automated and markerless systems are overcoming these drawbacks for conducting biomechanical studies,especially outside laboratories.Similarly,new posture analysis techniques are emerging,often driven by the need for fast and non-invasive methods to obtain high-precision results.These new technologies have also become effective for children or adolescents with non-specific back pain and postural insufficiencies.The evolutions of these methods aim to standardize measurements and provide manageable tools in clinical practice for the early diagnosis of musculoskeletal pathologies and to monitor daily improvements of each patient.Herein,these devices and their uses are described,providing researchers,clinicians,orthopedics,physical therapists,and sports coaches an effective guide to use new technologies in their practice as instruments of diagnosis,therapy,and prevention.

Reconfiguration of face expressions based on the discrete capture data of radial basis function interpolation

Compactly supported radial basis function can enable the coefficient matrix of solving weigh linear system to have a sparse banded structure, thereby reducing the complexity of the algorithm. Firstly, based on the compactly supported radial basis function, the paper makes the complex quadratic function （Multiquadric, MQ for short） to be transformed and proposes a class of compactly supported MQ function. Secondly, the paper describes a method that interpolates discrete motion capture data to solve the motion vectors of the interpolation points and they are used in facial expression reconstruction. Finally, according to this characteris- tic of the uneven distribution of the face markers, the markers are numbered and grouped in accordance with the density level, and then be interpolated in line with each group. The approach not only ensures the accuracy of the deformation of face local area and smoothness, but also reduces the time complexity of computing.

Introducing semantic information into motion graph

To improve motion graph based motion synthesis,semantic control was introduced.Hybrid motion features including both numerical and user-defined semantic relational features were extracted to encode the characteristic aspects contained in the character's poses of the given motion sequences.Motion templates were then automatically derived from the training motions for capturing the spatio-temporal characteristics of an entire given class of semantically related motions.The data streams of motion documents were automatically annotated with semantic motion class labels by matching their respective motion class templates.Finally,the semantic control was introduced into motion graph based human motion synthesis.Experiments of motion synthesis demonstrate the effectiveness of the approach which enables users higher level of semantically intuitive control and high quality in human motion synthesis from motion capture database.

Motion texture using symmetric property and graphcut algorithm

In this paper, a novel motion texture approach is presented for synthesizing long character motion (e.g., kungfu) that is similar to the original short input motion. First, a new motion with repeated frames is generated by exploiting the symmetric properties of the frames and reversing the motion sequence playback in a given motion sequence. Then, the order of the above motion sequence is rearranged by putting the start and the end frames together. The graphcut algorithm is used to seamlessly synthesize the transition between the start and the end frames, which is noted as graphcut-based motion-texton. Finally, we utilize the motion-textons to synthesize long motion texture, which can be patched together like the image texture synthesis method using graphcut algorithm, and automatically form a long motion texture endlessly. Our approach is demonstrated by synthesizing the long kungfu motion texture without visual artifacts, together with post-processing including our new developed graphcut-based motion blending and Poisson-based motion smoothing techniques.