Academic literature on the topic 'Motion capture (MoCap)'

Purpose Motion capture system (MoCap) has been used in measuring the human body segments in several applications including film special effects, health care, outer-space and under-water navigation systems, sea-water exploration pursuits, human machine interaction and learning software to help teachers of sign language. The purpose of this paper is to help the researchers to select specific MoCap system for various applications and the development of new algorithms related to upper limb motion. Design/methodology/approach This paper provides an overview of different sensors used in MoCap and techniques used for estimating human upper limb motion. Findings The existing MoCaps suffer from several issues depending on the type of MoCap used. These issues include drifting and placement of Inertial sensors, occlusion and jitters in Kinect, noise in electromyography signals and the requirement of a well-structured, calibrated environment and time-consuming task of placing markers in multiple camera systems. Originality/value This paper outlines the issues and challenges in MoCaps for measuring human upper limb motion and provides an overview on the techniques to overcome these issues and challenges.

The rapid technological advancements of Industry 4.0 have opened up new vectors for novel industrial processes that require advanced sensing solutions for their realization. Motion capture (MoCap) sensors, such as visual cameras and inertial measurement units (IMUs), are frequently adopted in industrial settings to support solutions in robotics, additive manufacturing, teleworking and human safety. This review synthesizes and evaluates studies investigating the use of MoCap technologies in industry-related research. A search was performed in the Embase, Scopus, Web of Science and Google Scholar. Only studies in English, from 2015 onwards, on primary and secondary industrial applications were considered. The quality of the articles was appraised with the AXIS tool. Studies were categorized based on type of used sensors, beneficiary industry sector, and type of application. Study characteristics, key methods and findings were also summarized. In total, 1682 records were identified, and 59 were included in this review. Twenty-one and 38 studies were assessed as being prone to medium and low risks of bias, respectively. Camera-based sensors and IMUs were used in 40% and 70% of the studies, respectively. Construction (30.5%), robotics (15.3%) and automotive (10.2%) were the most researched industry sectors, whilst health and safety (64.4%) and the improvement of industrial processes or products (17%) were the most targeted applications. Inertial sensors were the first choice for industrial MoCap applications. Camera-based MoCap systems performed better in robotic applications, but camera obstructions caused by workers and machinery was the most challenging issue. Advancements in machine learning algorithms have been shown to increase the capabilities of MoCap systems in applications such as activity and fatigue detection as well as tool condition monitoring and object recognition.

O Motion Capture (MoCap) é um sistema capaz de medir o deslocamento do ser humano. A tecnologia de captura de movimentos pode ser utilizada em produções de entretenimento digital, como os games e as animações 3D. Neste trabalho, busca-se sistematizar os níveis de interatividade possibilitadas a partir do equipamento óptico de captura de movimentos, analisando as variáveis descritas por Steuer (1992) e as definições de interatividade descritas por Lévy (2000), discutindo a interação do homem com o MoCap em termos de possibilidades de apropriação e de personalização, virtualidade, a implicação da imagem do participante e da telepresença. Os resultados permitem uma reflexão sobre o potencial de interatividade do sistema e concluindo com observações do alto potencial de interatividade do equipamento de Motion Capture.

Created with digital motion capture, or mocap, the virtual dances Ghostcatching and as.phyx.ia render movement abstracted from choreographic bodies. These depictions of gestural doubles or ‘ghosts’ trigger a sense of the uncanny rooted in mocap’s digital processes. Examining these material processes, this article argues that this digital optical uncanny precipitates from the intersubjective relationship of performer, technology, and spectator. Mocap interpolates living bodies into a technologized visual field that parses these bodies as dynamic data sets, a process by which performing bodies and digital capture technologies coalesce into the film’s virtual body. This virtual body signals a computational agency at its heart, one that choreographs the intersubjective embodiments of real and virtual dancers, and spectators. Destabilizing the human body as a locus of perception, movement, and sensation, mocap triggers uncanny uncertainty in human volition. In this way, Ghostcatching and as.phyx.ia reflect the infiltration of computer vision technologies, such as facial recognition, into numerous aspects of contemporary life. Through these works, the author hopes to show how the digital gaze of these algorithms, imperceptible to the human eye, threatens individual autonomy with automation.

This paper describes a motion capture (mocap) data-driven digital museum roaming system with high walking reality. We focus on three main questions: the animation of avatars; the path planning; and the collision detection among avatars. We use only a few walking clips from mocap data to synthesize walking motions with natural transitions, any direction and any length. Let the avatars roam in the digital museum with its Voronoi skeleton path, shortest path or offset path. And also we use Voronoi diagram to do collision detection. Different users can set up their own avatars and roam along their own path. We modify the motion graph method by classify the original mocap data and set up their motion graph which can improve search efficiency greatly.

The measurement of human motion is an important aspect of ergonomic mobility design, in which the mobility product is evaluated based on human factors obtained by digital human (DH) technologies. The optical motion-capture (MoCap) system has been widely used for measuring human motion in laboratories. However, it is generally difficult to measure human motion using mobility products in real-world scenarios, e.g., riding a bicycle on an outdoor slope, owing to unstable lighting conditions and camera arrangements. On the other hand, the inertial-measurement-unit (IMU)-based MoCap system does not require any optical devices, providing the potential for measuring riding motion even in outdoor environments. However, in general, the estimated motion is not necessarily accurate as there are many errors due to the nature of the IMU itself, such as drift and calibration errors. Thus, it is infeasible to apply the IMU-based system to riding motion estimation. In this study, we develop a new riding MoCap system using IMUs. The proposed system estimates product and human riding motions by combining the IMU orientation with contact constraints between the product and DH, e.g., DH hands in contact with handles. The proposed system is demonstrated with a bicycle ergometer, including the handles, seat, backrest, and foot pedals, as in general mobility products. The proposed system is further validated by comparing the estimated joint angles and positions with those of the optical MoCap for three different subjects. The experiment reveals both the effectiveness and limitations of the proposed system. It is confirmed that the proposed system improves the joint position estimation accuracy compared with a system using only IMUs. The angle estimation accuracy is also improved for near joints. However, it is observed that the angle accuracy decreases for a few joints. This is explained by the fact that the proposed system modifies the orientations of all body segments to satisfy the contact constraints, even if the orientations of a few joints are correct. This further confirms that the elapsed time using the proposed system is sufficient for real-time application.

To increase the efficiency of golf training, 3D swing reconstruction is broadly used among golf researchers. Traditional reconstruction methods apply motion capture system (MOCAP) to gain golfers motion data and drive bio-mechanical model directly. The cost of MOCAP system restricts the application area of golf research and the reconstruction quality of swing relies on the accuracy of the motion data. We introduced the dynamical analysis into swing reconstruction and proposed a Dynamic Bayesian Network (DBN) model with Kinect to capture the swing motion. Our model focused on modeling the bio-mechanical and dynamical relationships between key joints of golfer during swing. The positions of key joints were updated by the model and were used as motion data to reconstruct golf swing. Experimental results show that our results are comparable with the ones acquired by optical MOCAP system in accuracy and can reconstruct the golf swing with much lower cost.

With the development of human motion capture (MoCap) equipment and motion analysis technologies, MoCap systems have been widely applied in many fields, including biomedicine, computer vision, virtual reality, etc. With the rapid increase in MoCap data collection in different scenarios and applications, effective segmentation of MoCap data is becoming a crucial issue for further human motion posture and behavior analysis, which requires both robustness and computation efficiency in the algorithm design. In this paper, we propose an unsupervised segmentation algorithm based on limb-bone partition angle body structural representation and autoregressive moving average (ARMA) model fitting. The collected MoCap data were converted into the angle sequence formed by the human limb-bone partition segment and the central spine segment. The limb angle sequences are matched by the ARMA model, and the segmentation points of the limb angle sequences are distinguished by analyzing the good of fitness of the ARMA model. A medial filtering algorithm is proposed to ensemble the segmentation results from individual limb motion sequences. A set of MoCap measurements were also conducted to evaluate the algorithm including typical body motions collected from subjects of different heights, and were labeled by manual segmentation. The proposed algorithm is compared with the principle component analysis (PCA), K-means clustering algorithm (K-means), and back propagation (BP) neural-network-based segmentation algorithms, which shows higher segmentation accuracy due to a more semantic description of human motions by limb-bone partition angles. The results highlight the efficiency and performance of the proposed algorithm, and reveals the potentials of this segmentation model on analyzing inter- and intra-motion sequence distinguishing.

The rationale that governs motion of the organic in the cubical leans towards a transformation of the body in space, emphasizes its mathematical properties and highlights the potential to measure and plot movement – this is the work of a Motion Capture (MoCap) system. The translation in the MoCap studio from physical to virtual is facilitated by the MoCap suit, a device that determines the abstract cubical representation that drives first the neutral, and then the characterized avatar in screen space. The enabling nature of the suit, as apparatus, is a spatial phenomenon informed by Schlemmer’s abstract ‘native’ costume and his vision of the Tanzermensch as the most appropriate form to occupy cubical space. The MoCap suit is similarly native. It bridges the physical and virtual, provides a Victor Turner like threshold and connection between environments, enacting a spatial discourse facilitated by costume. This collision of Velcro, Avatar and Oskar Schlemmer allows a performance of space, binding historical modernity to contemporary practice. This performance of activated space is captured by a costume that endures, in Dorita Hannah’s words, despite the human form.

Motion Capture is an essential part of a world full of digital effects in movies and games. Understanding the pipelines between software is a crucial component of this research. Methods that create the motion capture structure today are reviewed, and how they are implemented in order to create the movements that we see in modern games and movies.

Il calcolo di questi valori è utile in quanto essi possono essere utilizzati per diversi scopi tra i quali la progettazione, ad esempio, di una stazione di assemblaggio in senso ergonomico focalizzando l’attenzione sulla salute dell’operatore. Possono inoltre fornire un valido supporto in sede di progettazione preliminare e di interventi correttivi del processo analizzato rilevando posture errate o potenzialmente dannose per l’operatore attraverso metodi più o meno empirici di valutazione del rischio.

[ES] La cirugía laparoscopia está considerada uno de los principales avances quirúrgicos en las últimas décadas. Esta técnica ha demostrado numerosas ventajas comparadas con la cirugía convencional abierta y ha sido extensamente usada para procesos quirúrgicos en el área abdominal. Para el paciente, la cirugía laparoscópica supone diversas ventajas, como por ejemplo menor dolor post operativo, tiempos de recuperación menores, menor riesgo de infección, o reducción del trauma. Para el cirujano en cambio, la situación es completamente diferente, esta práctica requiere mayor esfuerzo, concentración y estrés mental que la práctica convencional abierta. Además fuerza al cirujano a adoptar posiciones no-neutras en falanges, manos, muñecas, y brazos. Estas posturas no-neutras son la principal causa de fatiga muscular y aumentan el riesgo de problemas musculo-esqueléticos. Estos problemas han sido ampliamente estudiados por diferentes equipos de investigación, los cuales están tratando de mejorar la experiencia del cirujano en el quirófano. El enfoque utilizado en este estudio es diferente del utilizado anteriormente por la mayoría de estos equipos, los cuales suelen propones soluciones basadas en cambios ergonómicos con la intención de mejorar la geometría del mango de pistola convencional, ya que se considera ergonómicamente deficiente. El problema con este enfoque, es que las deficiencias no se encuentran únicamente en el mango, sino en la utilización de un punto de entrada fijo que fuerza a los cirujanos a mantener posiciones desfavorables. En este trabajo, se introduce el concepto "Libertad Postural" en el ámbito de la cirugía, este se basa en la hipótesis de que, si las herramientas no forzaran la posición de los cirujanos, estos mantendrían posiciones más favorables y cercanas al rango de posiciones neutras durante los procesos laparoscópicos. Los beneficios de este concepto han sido demostrados por medio de análisis de movimiento y de electromiografía de superficie, los cuales indican que la "Libertad Postural" es causante de un claro aumento de las posiciones neutras y de la reducción de la fatiga muscular, y han sido testeados por cirujanos en entornos simulados, los cuales encuentran beneficioso utilizar la "Libertad Postural" como característica base de este nuevo diseño de herramienta laparoscópica. En la sección final de este trabajo se propone un diseño que implementa el concepto de libertad postura con el cual se reduciría la fatiga muscular y los problemas musculo esqueléticos asociados a la práctica laparoscópica. Este diseño tiene la característica de actuar como una nueva sección del brazo, siendo una articulación que soporta los giros y grandes desplazamientos que normalmente tienen que desarrollar los brazos del cirujano. Además, esta solución es económica y fácil de fabricar, lo cual permitiría su uso por cirujanos de todo el mundo.
[CAT] La cirurgia laparoscòpia està considerada un dels principals avanços quirúrgics en les últimes dècades. Aquesta tècnica ha demostrat nombrosos avantatges comparats amb la cirurgia convencional oberta i ha sigut extensament usada per a processos quirúrgics en l'àrea abdominal. Per al pacient, la cirurgia laparoscòpica suposa diversos avantatges, com per exemple menor dolor post operatiu, temps de recuperació menors, menor risc d'infecció, o reducció del trauma. Per al cirurgià en canvi, la situació és completament diferent, aquesta pràctica requereix major esforç, concentració i estrés mental que la pràctica convencional oberta. A més força al cirurgià a adoptar posicions no-neutres en falanges, mans, nines, i braços. Aquestes postures no-neutres són la principal causa de fatiga muscular i augmenten el risc de problemes musculo-esquelètics. Aquests problemes han sigut àmpliament estudiats per diferents equips d'investigació, els quals estan tractant de millorar l'experiència del cirurgià en el quiròfan. L'enfocament utilitzat en aquest estudi és diferent de l'utilitzat anteriorment per la majoria d'aquests equips, els quals solen proposes solucions basades en canvis ergonòmics amb la intenció de millorar la geometria del mànec de pistola convencional, ja que es considera ergonòmicament deficient. El problema amb aquest enfocament, és que les deficiències no es troben únicament en el mànec, sinó en la utilització d'un punt d'entrada fix que força als cirurgians a mantindre posicions desfavorables. En aquest treball, s'introdueix el concepte "Llibertat Postural" en l'àmbit de la cirurgia, aquest es basa en la hipòtesi que, si les eines no forçaren la posició dels cirurgians, aquests mantindrien posicions més favorables i pròximes al rang de posicions neutres durant els processos laparoscòpics. Els beneficis d'aquest concepte han sigut demostrats per mitjà d'anàlisi de moviment i de electromiografía de superfície, els quals indiquen que la "Llibertat Postural" és causant d'un clar augment de les posicions neutres i de la reducció de la fatiga muscular, i han sigut testats per cirurgians en entorns simulats, els quals troben beneficiós utilitzar la "Llibertat Postural" com a característica base d'aquest nou disseny d'eina laparoscòpica. En la secció final d'aquest treball es proposa un disseny que implementa el concepte de llibertat postura amb el qual es reduiria la fatiga muscular i els problemes *musculo esquelètics associats a la pràctica laparoscòpica. Aquest disseny té la característica d'actuar com una nova secció del braç, sent una articulació que suporta els girs i grans desplaçaments que normalment han de desenvolupar els braços del cirurgià. A més, aquesta solució és econòmica i fàcil de fabricar, la qual cosa permetria el seu ús per cirurgians de tot el món.
[EN] Laparoscopic surgery is considered one of the main surgical advances in the last decades, this technique has demonstrated numerous advantages compared to open conventional surgery and it is widely used in abdominal procedures around the world. For the patient, laparoscopic surgery suppose less post-operative pain, shorter recovery time, lower risk of infection, and reduction of the trauma among other benefits. For the surgeon, the situation is completely different, this practice requires more effort, concentration and mental stress than conventional open procedures. It forces the surgeon to adopt non-neutral postures with phalanges, hands, wrists, and arms being this non-neutral postures the main cause of muscular fatigue and high risk of musculoskeletal disorders. The poor ergonomic postures accelerate muscle fatigue and pain because, outside the neutral range, muscles require more energy to generate the same contractile force than in neutral position. This increase of muscular fatigue is associated with the potential to commit errors that may harm the patient during the surgery. Because this problem is widely studied and different research centers are already trying to improve their surgeons experience in the operation room, the approach used during this work is different than most of the ones presented in previous works. Generally, the solutions proposed are based on ergonomic changes in the handle shape of the instrument, because the conventional pistol-grip handle is considered ergonomically poor. But the problem is not only in the shape of the handle but also in the fixed point of entrance that force the positions for the surgeon despite the handle¿s shape. In this work, the concept of postural freedom in laparoscopic surgery is introduced and evaluated. The postural freedom concept is based on the hypothesis that the surgeon involuntarily would maintain neutral postures if the instrument does not force him or her to reach extreme position with the upper limbs. The benefits of this concept has been demonstrated, by means of electromyography and motion capture. It reduces the localized muscular fatigue and increases the number of neutral postures during laparoscopic simulations. In the final section it is proposed a design that implements the postural freedom concept with, according on the results, the potential to reduce the localized muscular fatigue and the musculoskeletal problems associated to the practice. The design proposed here acts as a new section on the arm, being an articulation that support the turns and big displacements that currently suffer the surgeon¿s body. The solution is affordable and easy to manufacture and could be used by surgeons worldwide.
Pace Bedetti, HM. (2019). The effect of "Postural Freedom" in laparoscopic surgery [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/122312
TESIS

La Langue des Signes Française (LSF) représente une part de l'identité et de la culture de la communauté des sourds en France. L'un des moyens permettant de promouvoir cette langue est la génération de contenu par le biais de personnages virtuels appelés avatars signeurs. Le système que nous proposons s’intègre dans un projet plus général de synthèse gestuelle de la LSF par concaténation qui permet de générer de nouvelles phrases à partir d'un corpus de données de mouvements annotées et capturées via un dispositif de capture de mouvement basé marqueurs (MoCap) en éditant les données existantes. En LSF, l'expressivité faciale est le vecteur de nombreuses informations (e.g., affectives, clausales ou adjectivales), d'où son importance. Cette thèse a pour but d'intégrer l'aspect facial de la LSF au système de synthèse concaténative décrit précédemment. Ainsi, nous proposons une chaîne de traitement de l'information allant de la capture des données via un dispositif de MoCap jusqu'à l'animation faciale de l'avatar à partir de ces données et l'annotation automatique des corpus ainsi constitués. La première contribution de cette thèse concerne la méthodologie employée et la représentation par blendshapes à la fois pour la synthèse d'animations faciales et pour l'annotation automatique. Elle permet de traiter le système d'analyse / synthèse à un certain niveau d'abstraction, avec des descripteurs homogènes et signifiants. La seconde contribution concerne le développement d'une approche d'annotation automatique qui s'appuie sur la reconnaissance d'expressions faciales émotionnelles par des techniques d'apprentissage automatique. La dernière contribution réside dans la méthode de synthèse qui s'exprime comme un problème d'optimisation assez classique mais au sein duquel nous avons inclus une énergie basée laplacien quantifiant les déformations d'une surface en tant qu'énergie de régularisation
French Sign Language (LSF) represents part of the identity and culture of the deaf community in France. One way to promote this language is to generate signed content through virtual characters called signing avatars. The system we propose is part of a more general project of gestural synthesis of LSF by concatenation that allows to generate new sentences from a corpus of annotated motion data captured via a marker-based motion capture device (MoCap) by editing existing data. In LSF, facial expressivity is particularly important since it is the vector of numerous information (e.g., affective, clausal or adjectival). This thesis aims to integrate the facial aspect of LSF into the concatenative synthesis system described above. Thus, a processing pipeline is proposed, from data capture via a MoCap device to facial animation of the avatar from these data and to automatic annotation of the corpus thus constituted. The first contribution of this thesis concerns the employed methodology and the representation by blendshapes both for the synthesis of facial animations and for automatic annotation. It enables the analysis/synthesis scheme to be processed at an abstract level, with homogeneous and meaningful descriptors. The second contribution concerns the development of an automatic annotation method based on the recognition of expressive facial expressions using machine learning techniques. The last contribution lies in the synthesis method, which is expressed as a rather classic optimization problem but in which we have included

Ambitionen och målet med mitt projekt var att visualisera delar av en berättelse med hjälp av den senaste datortekniken. Detta tog sin form av en 3d-animation. Målet var inte att producera en färdig kortfilm utan att arbeta med utvalda delar. Projektet var indelat i tre block; en planerings- och researchfas, en produktionsfas och en reflektionsfas. Stora delar av magisterarbetet har bestått av att producera innehåll som sedan ska analyseras. Med arbetet vill jag att folk ska få mer förståelse för 3d-tekniken som ett flexibelt och intressant konstverktyg. I denna reflektion som är beroende av produktresultatet försöker jag i ord beskriva den tekniska och estetiska vägen från koncept till produktion. För att få förståelse för mina resonemang i denna reflektion kommer jag att använda mig av bilder från min produktion. Resultatet av magistern är en del av en arbetsprocess som kan analyseras och reflekteras. Med projektet har jag lärt mig att 3d inte är ett likriktat grafiskt verktyg utan en fascinerande konstform som är mer flexibel och personlig än vad man kan tro. Jag har funderat mycket kring det konstnärliga värdet i det jag har skapat och funderat mycket kring vad digital konst egentligen är och hur jag ser på det.
Detta är en reflektionsdel till en digital medieproduktion. cload@evilemail.com www.cloaddust.com

La animación facial es uno de los tópicos todavía no resueltos tanto en el campo de la interacción hombre máquina como en el de la informática gráfica. Las expresiones de alegría asociadas a risa y sonrisa son por su significado e importancia, parte fundamental de estos campos. En esta tesis se hace una aproximación a la representación de los diferentes tipos de risa en animación facial a la vez que se presenta un nuevo método capaz de reproducir todos estos tipos. El método se valida mediante la recreación de secuencias cinematográficas y mediante la utilización de bases de datos de expresiones faciales genéricas y específicas de sonrisa. Adicionalmente se crea una base de datos propia que recopila los diferentes tipos de risas clasificados y generados en este trabajo. De acuerdo a esta base de datos propia se generan las expresiones más representativas de cada una de las risas y sonrisas consideradas en el estudio.
L'animació facial és un dels tòpics encara no resolts tant en el camp de la interacció home màquina com en el de la informàtica gràfica. Les expressions d'alegria associades a riure i somriure són pel seu significat i importància, part fonamental d'aquests camps. En aquesta tesi es fa una aproximació a la representació dels diferents tipus de riure en animació facial alhora que es presenta un nou mètode capaç de reproduir tots aquests tipus. El mètode es valida mitjançant la recreació de seqüències cinematogràfiques i mitjançant la utilització de bases de dades d'expressions facials genèriques i específiques de somriure. Addicionalment es crea una base de dades pròpia que recull els diferents tipus de rialles classificats i generats en aquest treball. D'acord a aquesta base de dades pròpia es generen les expressions més representatives de cadascuna de les rialles i somriures considerades en l'estudi.
Nowadays, facial animation is one of the most relevant research topics still unresolved both in the field of human machine interaction and in the computer graphics. Expressions of joy associated with laughter and smiling are a key part of these fields mainly due to its meaning and importance. In this thesis an approach to the representation of different types of laughter in facial animation is done while a new method to reproduce all these types is proposed. The method is validated by recreating movie sequences and using databases of generic and specific facial smile expressions. Additionally, a proprietary database that lists the different types of classified and generated laughs in this work is created. According to this proprietary database the most representative of every smile expression considered in the study is generated.

The purpose of this paper is to examine and compare two simple motion capturesystems. The first system consists of two cameras, and the second system consists of acamera with a depth sensor. The problem with both systems is their limited field ofview. If the actor is facing a camera, that camera will not be able to see an arm if thatarm is placed behind the back.My method in order to do this examination, was to record a number of different typesof motions with both systems, and then evaluate and compare the generated data fromthe two systems. This was done partly by applying it to a 3D character, and partly byinvestigating how good incomplete data could be repaired. Some motions wasrecorded multiple times, each with a different angle. The examination has resulted indifferent conclusions about the two systems.The process of using two cameras was very time consuming and the actor had to standfacing the cameras more or less. The depth sensing camera was shown to be able tohandle a wider range of motions, and the angle relative to the cameras wasn't aslimited. Some advantages could be found compared to the depth sensing camera,which had troubles handling certain types of arm and head rotations. This waspossible to handle with two cameras.
Validerat; 20140627 (global_studentproject_submitter)

Dissertação de Mestrado em Design e Multimédia apresentada à Faculdade de Ciências e Tecnologia
Nesta dissertação é descrita toda a produção da curta-metragem de animação “A Caçada”, adaptada do conto homónimo de Miguel Torga, com principal foco nas técnicas de Computer-generated Imagery (CGI) e Motion Capture (MoCap).O objetivo passou por produzir uma curta-metragem de animação de raiz, experienciando as diferentes fases na produção de um filme, pré-produção, produção e pós-produção. Explorar CGI, MoCap e combinar cenários reais com personagens 3D. Adaptou-se o conto literário de Miguel Torga e desenvolveu-se um projeto de design de personagens.Esta dissertação surge, não só, mas também, para tirar partido de tecnologias como Computer-generated Imagery (CGI) e Motion Capture (MoCap), tecnologias que há poucos anos eram só acessíveis às grandes produções de cinema, propondo a produção duma curta-metragem que alia a tecnologia à forma mais clássica do cinema e aborda um conto de um autor sobejamente conhecido.Tal como referido anteriormente, o principal foco desta dissertação é desenvolver um projeto de design de personagens e adaptação a curta-metragem de animação digital. Explorando CGI e MoCap, combinação de cenários mistos, com o propósito de criar uma curta-metragem, adaptando o conto “A Caçada” do livro “Novos Contos da Montanha” de Miguel Torga (1944), fazendo uso das competências aprendidas.A dissertação tenta dar resposta a uma questão importante e, por vezes, decisiva: em que medida é possível fazer um filme de baixo custo, utilizando técnicas de Computer-generated Imagery (CGI) e Motion Capture (MoCap)?
This dissertation describes the entire production of the animated short film "A Caçada", adapted from Miguel Torga's homonymous tale, with a focus on Computer-generated Imagery (CGI) and Motion Capture (MoCap) techniques.The goal was to produce an animated short film from the beginning, experiencing the different stages in the production of a film, pre-production, production and post-production. Explore CGI, MoCap and combine real-world scenarios with 3D characters. Adapted the short story of Miguel Torga and developed a design of characters.This dissertation emerges, not only, but also to take advantage of technologies such as Computer-Generated Imagery (CGI) and Motion Capture (MoCap), technologies that only a few years ago were only accessible to major film productions, proposing the production of a short film that combines technology with the most classic form of cinema and addresses a well-known author's short story.As mentioned previously, the main focus of this dissertation is to develop a project of character design and adaptation to the short film of digital animation. Exploring CGI and MoCap, a combination of mixed scenarios, with the purpose of creating a short film, adapting the story "A Caçada" from the book "Novos Contos da Montanha" by Miguel Torga (1944), making use of the learned skills.The dissertation tries to answer an important and sometimes decisive question: to what extent is it possible to make a low-cost film using Computer-generated Imagery (CGI) and Motion Capture (MoCap)?

The main target of this thesis was to detect objective changes in the implementation of four postural locomotor tests DNS and during walking. The movements were recorded using the optical MoCap - the kinematic analysis Qualisys. The particular interest of the investigation was to determine the current stabilization of the spine system in individual subjects aged 25 to 55 years, which was documented by means of the angular deflection of each segment, the flat segment deviation or the shift of the marker in a coordinate system. The measurement results were compared between ten individuals with LBP and ten persons without any difficulty who were placed into the control group. The data were collected using the software QTM and Visual3D and subsequently were statistically processed. A statistically significant difference was observed during walking when comparing the angular deflection of the pelvis to the chest at the rotation and lateroflexion (ř). The significant difference of the pelvis shift toward the chest during flexion and rotation (ř) was showed in a deep squat test, but the difference was not confirmed in lateroflexion (ř). Furthermore, no statistical difference of the lateral deflection of the same segment (pelvis or chest) (cm) in patients with LBP compared to all subjects during the...

The motion capture (MoCap) is a highly popular subject with wide applications in different areas such as animations, situational awareness, and healthcare. An overview of MoCap utilizing different sensors and technologies is presented, and the prominent MoCap methods using inertial measurement units and optics are discussed in terms of their advantages and disadvantages. MoCap with wearable inertial measurement units is analyzed and presented specifically with the background information and methods. The chapter puts an emphasis on the mathematical model and artificial intelligence algorithms developed for the MoCap. Both the products from the important technology developers and the proof-of-concept applications conducted by Havelsan are presented within this chapter to involve an industrial perspective. MoCap system will act as a decision support system in either application by providing automatic calculation of metrics or classification, which are the basic tools for decision making.

This chapter studies the human walking motion that is unique for every individual and could be used for many medical and biometric applications. The authors’ goal is to develop a general low-dimensional (LD) model from of a set of high-dimensional (HD) motion capture (MoCap) data acquired from different individuals, where there are two main factors involved, i.e., pose (a specific posture in a walking cycle) and gait (a specific walking style). Many Gaussian process (GP)-based manifold learning methods have been proposed to explore a compact LD manifold embedding for motion representation where only one factor (i.e., pose) is normally revealed explicitly with the other factor (i.e., gait) implicitly or independently treated. The authors recently proposed a new GP-based joint gait-pose manifold (JGPM) that unifies these two variables into one manifold structure to capture the coupling effect between them. As the result, JGPM is able to capture the motion variability both across different poses and among multiple gaits (i.e., individuals) simultaneously. In order to show advantages of joint modeling of combining the two factors in one manifold, they develop a validation technique to compare JGPM with recent GP-based methods in terms of their capability of motion interpolation, extrapolation, denoising, and recognition. The experimental results further demonstrate advantages of the proposed JGPM for human motion modeling.

The way a person moves, either in a plain walk or performing a specific task, tells a huge quantity of information about his/her physical and, eventually, neurologic condition. A large part of a physiotherapist work of assessment is based on the qualitative evaluation, mainly visual, of a person’s movements, in terms of balance, speed, control, force and other parameters. This research work aims at providing personnel involved in the rehab process with a quantitative method to assess the way movements are performed. A numerical measure of the performance, actually, allows easier and more precise assessment, eliminating bias due to subjectivity. To accomplish this goal two steps are required: 3D acquisition of the movement using a Motion Capture (Mocap) system, and analysis of collected data to extract or elaborate the final outcome in the form requested by the medical staff. The paper shows the way Mocap acquisition are performed and data are analyzed in the application with people having a complete spinal cord injury and using a wheelchair. The method has been tested with eight volunteers in the rehabilitation department of the Hospital Papa Giovanni XXIII in Bergamo, Italy.

Using a wheelchair can be a challenging task for people with reduced force and control of muscles of abdomen or lower back. Spinal cord injured (SCI) people are the majority of those who are spending most of the day on a wheelchair and a proper training and chair setup is mandatory to reach a good level of functionality and to avoid harms and side effects. In order to assess the complex motion of a person self-pushing a wheelchair, a motion capture (Mocap) system has been arranged and a group of SCI patients has been acquired in a hospital gym. The Mocap system uses three Microsoft Kinect RGB-D sensors and iPisoft to perform the recording of the 3D motion. The main goal of the research is to provide therapists with a quantitative method to define a preliminary configuration in an objective way once is given the user’s medical conditions and his/her way of using the wheelchair. Working side by side with physiotherapists, the main parameters to be evaluated (e.g. pushing angles) have been identified and algorithms have been identified to automatically extract them from the 3D digital avatar model data coming from the Mocap system. The performance of the patients is then analyzed taking into account the wheelchair setup (e.g. position and inclination of the seat and of the back). The influence of geometric parameters on patients’ motion is analyzed so that design guidelines for configuration can be found. The overall outcome is to maximize performance and minimize side effects and fatigue, providing users with a better experience on the wheelchair.

Abstract Low cost marker-less motion capture (Mocap) systems can be considered an interesting technology for the objective assessment of rehabilitation processes. In particular, this paper presents a feasibility study to introduce a Mocap system as a tool to assess shoulder rehabilitation. The movements of a shoulder are complex and challenging to be captured with a marker-less system because the skeleton avatar usually oversimplifies shoulder articulation with a single virtual joint. The designed solution integrates a low-cost Mocap system with image processing techniques and convolutional neural networks to automatically detect and measure potential compensatory movements executed during an abduction, which is one of the first post-surgery exercises for shoulder rehabilitation. First, we introduce the main steps of a reference roadmap that guided the development of the Mocap solution for rehab assessment of injured shoulder. Then, the acquisition of medical knowledge is presented as well as the new Mocap solution based on the integration of convolutional neural networks and 2D motion tracking techniques. Finally, the application which automatically evaluates abductions and makes available the measurements of the scapular elevations is described. Preliminary study and future works are also presented and discussed.

Abstract In the last years, the advent of low-cost markerless motion capture systems fostered their use in several research fields, such as healthcare and sport. Any system presents benefits and drawbacks that have to be considered to design a Mocap solution providing a proper motion acquisition for a specific context. In order to evaluate low-cost technology, this research work focuses on the evaluation of the accuracy of two categories of devices: the RGB active cameras and the RGB-D, or depth sensors devices. In particular, GoPro Hero 6 active cameras and Microsoft Kinect v2 devices have been selected as representative of the two categories. In particular, this work evaluates and compares the performances of the two systems used to track the position of human articulations. The two devices have been chosen among those available on the market after a state of the art has been completed. Before starting with the campaign of acquisition, the number of sensors and their layout have been designed to optimize the acquisition with both mark-less Mocap systems. Their comparison is based on a list of specific movements of upper and lower limbs. Each movement has been acquired simultaneously, to guarantee the same test conditions. The results have been organized, compared and discussed by evaluating performances and limitations of both solutions related to specific context of use. Conclusions highlight the best candidate technology.

A number of pathologies impact on the way a patient can either move or control the movements of the body. Traumas, articulation arthritis or generic orthopedic disease affect the way a person can walk or perform everyday movements; brain or spine issues can lead to a complete or partial impairment, affecting both muscular response and sensitivity. Each of these disorder shares the need of assessing patient’s condition while doing specific tests and exercises or accomplishing everyday life tasks. Moreover, also high-level sport activity may be worth using digital tools to acquire physical performances to be improved. The assessment can be done for several purpose, such as creating a custom physical rehabilitation plan, monitoring improvements or worsening over time, correcting wrong postures or bad habits and, in the sportive domain to optimize effectiveness of gestures or related energy consumption. The paper shows the use of low-cost motion capture techniques to acquire human motion, the transfer of motion data to a digital human model and the extraction of desired information according to each specific medical or sportive purpose. We adopted the well-known and widespread Mocap technology implemented by Microsoft Kinect devices and we used iPisoft tools to perform acquisition and the preliminary data elaboration on the virtual skeleton of the patient. The focus of the paper is on the working method that can be generalized to be adopted in any medical, rehabilitative or sportive condition in which the analysis of the motion is crucial. The acquisition scene can be optimized in terms of size and shape of the working volume and in the number and positioning of sensors. However, the most important and decisive phase consist in the knowledge acquisition and management. For each application and even for each single exercise or tasks a set of evaluation rules and thresholds must be extracted from literature or, more often, directly form experienced personnel. This operation is generally time consuming and require further iterations to be refined, but it is the core to generate an effective metric and to correctly assess patients and athletes performances. Once rules are defined, proper algorithms are defined and implemented to automatically extract only the relevant data in specific time frames to calculate performance indexes. At last, a report is generated according to final user requests and skills.

Human motion capture (mocap) data, recording the movement of markers attached to specific joints, has gradually become the most popular solution of animation production. However, the raw motion data are often corrupted due to joint occlusion, marker shedding and the lack of equipment precision, which severely limits the performance in real-world applications. Since human motion is essentially a sequential data, the latest methods resort to variants of long short-time memory network (LSTM) to solve related problems, but most of them tend to obtain visually unreasonable results. This is mainly because these methods hardly capture long-term dependencies and cannot explicitly utilize relevant context, especially in long sequences. To address these issues, we propose a deep bi-directional attention network (BAN) which can not only capture the long-term dependencies but also adaptively extract relevant information at each time step. Moreover, the proposed model, embedded attention mechanism in the bi-directional LSTM (BLSTM) structure at the encoding and decoding stages, can decide where to borrow information and use it to recover corrupted frame effectively. Extensive experiments on CMU database demonstrate that the proposed model consistently outperforms other state-of-the-art methods in terms of recovery accuracy and visualization.

Up-down and rifle aiming maneuvers are common tasks employed by soldiers and athletes. The movements underlying these tasks largely determine performance success, which motivates the need for a noninvasive and portable means for movement quantification. We answer this need by exploiting body-worn and rifle-mounted miniature inertial measurement units (IMUs) for measuring torso and rifle motions during up-down and aiming tasks. The IMUs incorporate MEMS accelerometers and angular rate gyros that measure translational acceleration and angular velocity, respectively. Both sensors enable independent estimates of the orientation of the IMU and thus, the orientation of a subject’s torso and rifle. Herein, we establish the accuracy of a complementary filter which fuses these estimates for tracking torso and rifle orientation by comparing IMU-derived and motion capture-derived (MOCAP) torso pitch angles and rifle elevation and azimuthal angles during four up-down and rifle aiming trials for each of 16 subjects (64 trials total). The up-down trials consist of five maximal effort get-down-get-up cycles (from standing to lying prone back to standing), while the rifle aiming trials consist of rapidly aiming five times at two targets 15 feet from the subject and 180 degrees apart. Results reveal that this filtering technique yields warfighter torso pitch angles that remain within 0.55 degrees of MOCAP estimates and rifle elevation and azimuthal angles that remain within 0.44 and 1.26 degrees on average, respectively, for the 64 trials analyzed. We further examine potential remaining error sources and limitations of this filtering approach. These promising results point to the future use of this technology for quantifying motion in naturalistic environments. Their use may be extended to other applications (e.g., sports training and remote health monitoring) where noninvasive, inexpensive, and accurate methods for reliable orientation estimation are similarly desired.

Abstract Nowadays, healthcare centers are not familiar with quantitative approaches for patients’ gait evaluation. There is a clear need for methods to obtain objective figures characterizing patients’ performance. Actually, there are no diffused methods for comparing the pre- and post-operative conditions of the same patient, integrating clinical information and representing a measure of the efficiency of functional recovery, especially in the short-term distance of the surgical intervention. To this aim, human motion tracking for medical analysis is creating new frontiers for potential clinical and home applications. Motion Capture (Mocap) systems are used to allow detecting and tracking human body movements, such as gait or any other gesture or posture in a specific context. In particular, low-cost portable systems can be adopted for the tracking of patients’ movements. The pipeline going from tracking the scene to the creation of performance scores and indicators has its main challenge in the data elaboration, which depends on the specific context and to the detailed performance to be evaluated. The main objective of this research is to investigate whether the evaluation of the patient’s gait through markerless optical motion capture technology can be added to clinical evaluations scores and if it is able to provide a quantitative measure of recovery in the short postoperative period. A system has been conceived, including commercial sensors and a way to elaborate data captured according to caregivers’ requirements. This allows transforming the real gait of a patient right before and/or after the surgical procedure into a set of scores of medical relevance for his/her evaluation. The technical solution developed in this research will be the base for a large acquisition and data elaboration campaign performed in collaboration with an orthopedic team of surgeons specialized in hip arthroplasty. This will also allow assessing and comparing the short run results obtained by adopting different state-of-the-art surgical approach for the hip replacement.