Use of Motion Capture in 3D Animation: Motion Capture Systems, Challenges, and Recent Trends

Sharma, Shubham; Verma, Shubhankar; Kumar, Mohit; Sharma, Lavanya

doi:10.1109/comitcon.2019.8862448

Cited by 38 publications

(15 citation statements)

References 10 publications

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“…Marker-basierte Systeme setzen ein hohes Maß an Expertenwissen voraus, da die Bewegungsmessqualität stark von der Ausrichtung der Kameras sowie von der Positionierung der Marker abhängt. Hauptsächlich finden Markerbasierte Systeme Anwendung in biomechanischen Laboren zur Ganganalyse (Singh et al, 2018;Vicon Motion Systems, 2010) oder in der Filmbranche für die Entwicklung von Animationen (Sharma et al, 2019). Marker-freie Systeme umfassen Bewegungsaufnahmeverfahren, die auf Bild-oder Videodaten bauen, dabei aber ohne Marker zur Bestimmung von relevanten Körperpositionen auskommen.…”

Section: Was Ist Und Kann Technologie-gestütztes Training?unclassified

Technologiegestütztes funktionelles Training in den eigenen vier Wänden

Venek¹,

Rieser²

2022

Aktives Altern Im Digitalen Zeitalter

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ZusammenfassungInternationale wie nationale Bewegungsempfehlungen unterstreichen den Faktor Bewegung für ein gesundes Altern. Durch Technologie-gestütztes Training sollen Barrieren zur Etablierung von Trainingsroutinen im Alltag überwunden und Nutzer*innen zu regelmäßiger Aktivität angeregt werden. Daher widmet sich dieser Beitrag der Definition und Einteilung von Technologie-gestütztem Fitnesstraining in den eigenen vier Wänden. Im Rahmen des fit4AAL-Projektes wurde ein solches Trainingssystem entwickelt, erprobt und die Trainingsdaten analysiert. Das in fit4AAL entwickelte personalisierte Trainingsprogramm dient als Beispiel einer komplexen digitalen Unterstützung.

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Section: Was Ist Und Kann Technologie-gestütztes Training?unclassified

Technologiegestütztes funktionelles Training in den eigenen vier Wänden

Venek¹,

Rieser²

2022

Aktives Altern Im Digitalen Zeitalter

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“…Three-dimensional (3D) motion capture video-based systems are generally considered the reference/gold standard in gait assessment, consistently demonstrating validity and reproducibility in a range of applications (Baskwill et al, 2017 ; Albert et al, 2020 ; Jakob et al, 2021 ). However, the use of a 3D motion tracking system demonstrates obvious pragmatic issues through high costs, an intrusive nature (i.e., users must be fitted with a range of anatomical markers), as well as the need for technical expertise (Schlagenhauf et al, 2018 ; Sharma et al, 2019 ), limiting the use of technology in low-resource, real-world settings. As such, wearable inertial measurement units (IMU) have seen a recent usage uptake in running gait assessment by providing a low-cost apparatus capable of detecting intricate running gait outcomes (Young et al, 2020 ; Benson et al, 2022 ).…”

Section: Introductionmentioning

confidence: 99%

Examination of a foot mounted IMU-based methodology for a running gait assessment

Young

Mason

Wall

et al. 2022

Front. Sports Act. Living

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Gait assessment is essential to understand injury prevention mechanisms during running, where high-impact forces can lead to a range of injuries in the lower extremities. Information regarding the running style to increase efficiency and/or selection of the correct running equipment, such as shoe type, can minimize the risk of injury, e.g., matching a runner's gait to a particular set of cushioning technologies found in modern shoes (neutral/support cushioning). Awareness of training or selection of the correct equipment requires an understanding of a runner's biomechanics, such as determining foot orientation when it strikes the ground. Previous work involved a low-cost approach with a foot-mounted inertial measurement unit (IMU) and an associated zero-crossing-based methodology to objectively understand a runner's biomechanics (in any setting) to learn about shoe selection. Here, an investigation of the previously presented ZC-based methodology is presented only to determine general validity for running gait assessment in a range of running abilities from novice (8 km/h) to experienced (16 km/h+). In comparison to Vicon 3D motion tracking data, the presented approach can extract pronation, foot strike location, and ground contact time with good [ICC(2,1) > 0.750] to excellent [ICC(2,1) > 0.900] agreement between 8–12 km/h runs. However, at higher speeds (14 km/h+), the ZC-based approach begins to deteriorate in performance, suggesting that other features and approaches may be more suitable for faster running and sprinting tasks.

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“…Motion capture systems are widely used in different fields and disciplines, including film, animation, video games, health (mainly in rehabilitation processes), and sports science, among others [1][2][3]. These systems have evolved from the appearance of the rotoscope in 1915, used in the entertainment industry [4], to the latest systems with increasingly better characteristics used in various knowledge fields.…”

Section: Introductionmentioning

confidence: 99%

A Kinematic Information Acquisition Model That Uses Digital Signals from an Inertial and Magnetic Motion Capture System

Alarcón-Aldana

Callejas-Cuervo

Bastos

et al. 2022

Sensors

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This paper presents a model that enables the transformation of digital signals generated by an inertial and magnetic motion capture system into kinematic information. First, the operation and data generated by the used inertial and magnetic system are described. Subsequently, the five stages of the proposed model are described, concluding with its implementation in a virtual environment to display the kinematic information. Finally, the applied tests are presented to evaluate the performance of the model through the execution of four exercises on the upper limb: flexion and extension of the elbow, and pronation and supination of the forearm. The results show a mean squared error of 3.82° in elbow flexion-extension movements and 3.46° in forearm pronation-supination movements. The results were obtained by comparing the inertial and magnetic system versus an optical motion capture system, allowing for the identification of the usability and functionality of the proposed model.

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Use of Motion Capture in 3D Animation: Motion Capture Systems, Challenges, and Recent Trends

Cited by 38 publications

References 10 publications

Technologiegestütztes funktionelles Training in den eigenen vier Wänden

Technologiegestütztes funktionelles Training in den eigenen vier Wänden

Examination of a foot mounted IMU-based methodology for a running gait assessment

A Kinematic Information Acquisition Model That Uses Digital Signals from an Inertial and Magnetic Motion Capture System

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