Using biomechanical constraints to improve video-based motion capture

In motion capture applications whose aim is to recover human body postures from various input, the high dimensionality of the problem makes it desirable to reduce the size of the search-space by eliminating a priori impossible configurations. This can be carried out by constraining the posture recovery process in various ways. Most recent work in this area has focused on applying camera viewpoint-related constraints to eliminate erroneous solutions. When camera calibration parameters are available, they provide an extremely efficient tool for disambiguating not only posture estimation, but also 3D reconstruction and data segmentation. Increased robustness is indeed to be gained from enforcing such constraints, which we prove in the context of an optical motion capture framework. Our contribution in this respect resides in having applied such constraints consistently to each main step involved in a motion capture process, namely marker reconstruction and segmentation, followed by posture recovery. These steps are made inter-dependent, where each one constrains the other. A more application-independent approach is to encode constraints directly within the human body model, such as limits on the rotational joints. This being an almost unexplored research subject, our efforts were mainly directed at determining a new method for measuring, representing and applying such joint limits. To the present day, the few existing range of motion boundary representations present severe drawbacks that call for an alternative formulation. The joint limits paradigm we propose not only overcomes these drawbacks, but also allows to capture intra- and inter-joint rotation dependencies, these being essential to realistic joint motion representation. The range of motion boundary is defined by an implicit surface, its analytical expression enabling us to readily establish whether a given joint rotation is valid or not. Furthermore, its continuous and differentiable nature provides us with a means of elegantly incorporating such a constraint within an optimisation process for posture recovery. Applying constrained optimisation to our body model and stereo data extracted from video sequence, we demonstrate the clearly resulting decrease in posture estimation errors. As a bonus, we have integrated our joint limits representation in character animation packages to show how motion can be naturally constrained in this manner

RESEARCH ON VIDEO-BASED HUMAN BODY MOTION TRACKING

The video-based motion capture system uses cheap equipments, like digital cameras and personal computers, to track a human motion without any sensors or markers attached to the body. This topic has a wide application in areas such as smart surveillance, human computer interaction and athletic performance analysis etc., and it becomes a hot topic of computer vision in recent years. Because of the complexity of the problem and lack of comprehension of human vision system essence, visual tracking is still hard in computer vision

A Quasi-Static Method for Determining the Characteristics of a Motion Capture Camera System in a "Split-Volume" Configuration

To confidently report any data collected from a video-based motion capture system, its functional characteristics must be determined, namely accuracy, repeatability and resolution. Many researchers have examined these characteristics with motion capture systems, but they used only two cameras, positioned 90 degrees to each other. Everaert used 4 cameras, but all were aligned along major axes (two in x, one in y and z). Richards compared the characteristics of different commercially available systems set-up in practical configurations, but all cameras viewed a single calibration volume. The purpose of this study was to determine the accuracy, repeatability and resolution of a 6-camera Motion Analysis system in a split-volume configuration using a quasistatic methodology

ASSESSMENT OF KINEMATIC CMJ DATA USING A DEEP LEARNING ALGORITHM-BASED MARKERLESS MOTION CAPTURE SYSTEM

The purpose of this study was to compare the performance of a 2D video-based markerless motion capture system to a conventional marker-based approach during a counter movement jump (CMJ). Twenty-three healthy participants performed CMJ while data were collected simultaneously via a marker-based (Oqus) and a 2D video-based motion capture system (Miqus, both: Qualisys AB, Gothenburg, Sweden). The 2D video data was further processed using Theia3D (Theia Markerless Inc.), both sets of data were analysed concurrently in Visual3D (C-motion, Inc). Excellent agreement between systems with ICCs \u3e0.988 exists for Jump height (mean average error of 0.35 cm) and ankle and knee sagittal plane angles (RMS differences \u3c 5°). The hip joint showed highe

Assessing the Utility of a Video-Based Motion Capture Alternative in the Assessment of Lumbar Spine Planar Angular Joint Kinematics

Markerless motion capture is a novel technique to measure human movement kinematics. The purpose of this research is to evaluate the markerless algorithm, DeepLabCut (DLC) against a 3D motion capture system (Vicon Motion Systems Ltd., Oxford, UK) in the analysis of planar spine and elbow flexion-extension movement. Data were acquired concurrently from DLC and Vicon for all movements. A novel DLC model was trained using data derived from a subset of participants (training group). Accuracy and precision were assessed from data derived from the training group as well as in a new set of participants (testing group). Two-way SPM ANOVAs were used to detect significant differences between the training vs. testing sets, capture methods (Vicon vs. DLC), as well as potential higher order interaction effect between these independent variables in the estimation of flexion extension angles and variability. No significant differences were observed in any planar angles, nor were any higher order interactions observed between each motion capture modality and the training vs. testing datasets. Bland Altman plots were also generated to depict the mean bias and level of agreement between DLC and Vicon for both training, and testing datasets. Supplemental analyses, suggest that these results are partially affected by the alignment of each participant’s body segments with respect to each planar reference frame. This research suggests that DLC-derived planar kinematics of both the elbow and lumbar spine are of acceptable accuracy and precision when compared to conventional laboratory gold-standards (Vicon)

An Approach for Identifying Gait Events Using Wavelet Denoising Technique and Single Wireless IMU

A new approach is proposed to identify gait events in non-laboratory environments with a single inertial measurement unit (IMU) embedded inside shoe. The aim of our work is to develop a useful clinical tool for monitoring individuals walking disability and detect specific pathological gait patterns. Temporal parameters of gait are determined by classification of accelerations and angular velocities. Wavelets denoising of IMU signals allows for an important amount of information that is exploited in different manners for event identification. It was found that wavelet denoising enhanced specific turning points which could effectively identify gait events. The method is verified by comparing the results of video-based motion capture system and force plates as conventional standards. This portable gait-monitoring system allows for versatile application beyond gait laboratory

ASSESSMENT OF KINEMATIC CMJ DATA USING A DEEP LEARNING ALGORITHM-BASED MARKERLESS MOTION CAPTURE SYSTEM

The purpose of this study was to compare the performance of a video-based markerless motion capture system to a conventional marker-based approach during a counter movement jump (CMJ). Twenty-three healthy participants performed CMJ while data was collected simultaneously via a marker-based (Oqus) and a 2D video-based motion capture system (Miqus, both: Qualisys). The video data was further processed to 3D-data using Theia3D (Theia Markerless Inc.). Excellent agreement between systems with ICCs \u3e0.99 exists for jump height (mean average error of -0.27 cm) and sagittal ankle and knee plane angles (RMSD \u3c 5°). The hip joint showed an average RMSD of 21° with a strong correlation of 0.80. As such the markerless system is capable of detecting jump height, sagittal ankle and knee joint angles and 3D joint positions of a CMJ to a high accurac

Investigating Grip Range of Motion and Force Exerted by Individuals with and without Hand Arthritis during Functional Tasks and while Swinging a Golf Club

Hand arthritis is the leading cause of disability in individuals over the age of 50; resulting in dysfunction and pain, making activities of daily living and recreational activities such as golf difficult. Few studies have been conducted on the biomechanical response of individuals with hand arthritis when performing functional activities. This research quantified hand grip movements and strength differences seen in individuals with hand arthritis. Using a video-based motion capture system (Dartfish), a grip limitation of 17.2% (maximum flexion), and 12.7% (maximum extension) was discovered. A wireless finger force measurement system (FingerTPS), was used to show that larger diameter, softer firmness golf grips assisted in reducing the grip force in individuals with and without hand arthritis during a golf swing. This research will benefit the sport biomechanics and clinical fields, providing quantitative results to develop more sophisticated joint protection devices and gain a better understanding of hand arthritis mechanics

Human-activity-centered measurement system:challenges from laboratory to the real environment in assistive gait wearable robotics

Assistive gait wearable robots (AGWR) have shown a great advancement in developing intelligent devices to assist human in their activities of daily living (ADLs). The rapid technological advancement in sensory technology, actuators, materials and computational intelligence has sped up this development process towards more practical and smart AGWR. However, most assistive gait wearable robots are still confined to be controlled, assessed indoor and within laboratory environments, limiting any potential to provide a real assistance and rehabilitation required to humans in the real environments. The gait assessment parameters play an important role not only in evaluating the patient progress and assistive device performance but also in controlling smart self-adaptable AGWR in real-time. The self-adaptable wearable robots must interactively conform to the changing environments and between users to provide optimal functionality and comfort. This paper discusses the performance parameters, such as comfortability, safety, adaptability, and energy consumption, which are required for the development of an intelligent AGWR for outdoor environments. The challenges to measuring the parameters using current systems for data collection and analysis using vision capture and wearable sensors are presented and discussed

Nasolabial Fold Dynamics: Implications for Facial Paralysis and Facial Reanimation Surgery

ObjectivesIn patients with facial paralysis, facial reanimation surgery may be needed to normalize facial soft tissue function/movements. Critical for this normalization is the dynamics of the nasolabial folds (NLFs). The objective of this prospective, observational study was to determine the 3D morphologic dynamics of the NLFs in patients with unilateral facial palsy and normal subjects.Settings and Sample Population3D facial soft tissue movement data collected from adults with unilateral, facial paralysis (Bell's Palsy, n=36); and (2) an age‐ and sex‐frequency matched control group (n=68).Materials and MethodsMovement data were collected during repeated animations from participants using a video‐based motion capture system. Movement in terms of displacement and asymmetry of the NLFs, nasal, and circumoral regions were analyzed in the lateral, vertical and depth planes; as well as movement of the commissure and NLFs relative to the lower lip midline. Two sample t tests were used to test for significant group differences.ResultsPatients NLFs had less mean displacement, greater mean asymmetry, and uncoordinated movements compared with the controls. For both groups during smiling, the NLF and commissure landmarks had approximately similar magnitudes of displacement (control range = 11‐14mm; patient range = 7‐10mm).ConclusionNLF dynamics during smiling were as significant as oral commissure excursion. Thus, an immobile NLF is an unnatural feature of facial animations. Surgical treatments that address impaired NFL movements must be considered to create a more natural surgical outcome especially during smiling.<br/