There is currently a wide variety of six degree-of-freedom (6-DOF) motion capture technologies available. However, these systems tend to be very expensive and thus cost prohibitive. A software system was developed to provide 6-DOF motion capture using the Nintendo Wii remote’s (wiimote) sensors, an infrared beacon, and a novel hierarchical linear-quaternion Kalman filter. The software is made freely available, and the hardware costs less than one hundred dollars. Using this motion capture software, a robotic control system was developed to teleoperate a 6-DOF robotic manipulator via the operator’s natural hand movements. The teleoperation system requires calibration of the wiimote’s infrared cameras to obtain an estimate of the wiimote’s 6-DOF pose. However, since the raw images from the wiimote’s infrared camera are not available, a novel camera-calibration method was developed to obtain the camera’s intrinsic parameters, which are used to obtain a low-accuracy estimate of the 6-DOF pose. By fusing the low-accuracy estimate of 6-DOF pose with accelerometer and gyroscope measurements, an accurate estimation of 6-DOF pose is obtained for teleoperation. Preliminary testing suggests that the motion capture system has an accuracy of less than a millimetre in position and less than one degree in attitude. Furthermore, whole-system tests demonstrate that the teleoperation system is capable of controlling the end effector of a robotic manipulator to match the pose of the wiimote. Since this system can provide 6-DOF motion capture at a fraction of the cost of traditional methods, it has wide applicability in the field of robotics and as a 6-DOF human input device to control 3D virtual computer environments.

3D Motion capture is a medium that plots motion, typically human motion, converting it into a form that can be represented digitally. It is a fast evolving field and recent inertial technology may provide new artistic possibilities for its use in live performance. Although not often used in this context, motion capture has a combination of attributes that can provide unique forms of collaboration with performance arts. The inertial motion capture suit used for this study has orientation sensors placed at strategic points on the body to map body motion. Its portability, real-time performance, ease of use, and its immunity from line-of-sight problems inherent in optical systems suggest it would work well as a live performance technology. Many animation techniques can be used in real-time. This research examines a broad cross-section of these techniques using four practice-led cases to assess the suitability of inertial motion capture to live performance. Although each case explores different visual possibilities, all make use of the performativity of the medium, using either an improvisational format or interactivity among stage, audience and screen that would be difficult to emulate any other way. A real-time environment is not capable of reproducing the depth and sophistication of animation people have come to expect through media. These environments take many hours to render. In time the combination of what can be produced in real-time and the tools available in a 3D environment will no doubt create their own tree of aesthetic directions in live performance. The case study looks at the potential of interactivity that this technology offers.

Biometrics is a unique physical or behavioral characteristic of a person. This unique attribute, such as fingerprints or gait, can be used for identification or verification purposes. Gait is an emerging biometrics with great potential. Gait recognition is based on recognizing a person by the manner in which they walk. Its potential lays in that it can be captured at a distance and does not require the cooperation of the subject. This advantage makes it a very attractive tool for forensic cases and applications, where it can assist in identifying a suspect when other evidence such as DNA, fingerprints, or a face were not attainable. Gait can be used for recognition in a direct manner when the two samples are shot from similar camera resolution, position, and conditions. Yet in some cases, the only sample available is of an incomplete gait cycle, low resolution, low frame rate, a partially visible subject, or a single static image. Most of these conditions have one thing in common: static measurements. A gait signature is usually formed from a number of dynamic and static features. Static features are physical measurements of height, length, or build; while dynamic features are representations of joint rotations or trajectories. The aim of this thesis is to study the potential of predicting dynamic features from static features. In this thesis, we have created a database that utilizes a 3D laser scanner for capturing accurate shape and volumes of a person, and a motion capture system to accurately record motion data. The first analysis focused on analyzing the correlation between twenty-one 2D static features and eight dynamic features. Eleven pairs of features were regarded as significant with the criterion of a P-value less than 0.05. Other features also showed a strong correlation that indicated the potential of their predictive power. The second analysis focused on 3D static and dynamic features. Through the correlation analysis, 1196 pairs of features were found to be significantly correlated. Based on these results, a linear regression analysis was used to predict a dynamic gait signature. The predictors chosen were based on two adaptive methods that were developed in this thesis: "the top-x" method and the "mixed method". The predictions were assessed for both for their accuracy and their classification potential that would be used for gait recognition. The top results produced a 59.21% mean matching percentile. This result will act as baseline for future research in predicting a dynamic gait signature from static features. The results of this thesis bare potential for applications in biomechanics, biometrics, forensics, and 3D animation.

Hip impingement is a hip associated abnormality which develops among young and middle-aged individuals. It reduces the activity of those affected and if it is not detected at early stage, it can result in osteoarthritis. In this thesis a reliable framework for studying impingement detection is developed. Current clinical methods in detecting hip impingement involve measuring three angles, first the patient’s leg being flexed until maximum angle, second patient’s leg being flexed until 90° then adducted until maximum angle, and third patient’s leg being flexed until 90° afterwards internally rotated until the maximum angle also known as FADIR (Flexion, adduction in 90° flexion and internal rotation in 90° flexion) test. This is a manual method and relies heavily on surgeons experience and even pain tolerance of the patient and the method is prone to error. The use of computational programmes are known to be more accurate and reliable as the kinematic of contact can easily be studied using the digitised bones of the hip joint assuming that the impingement is determined by bone to bone contact kinematics. Current impingement studies assume that the kinematics of hip joint can be studied by assuming the centre of rotation is fixed for hip joint. For highly conforming joints this assumption is acceptable but for cases where conformity is poor the presence of soft tissue and soft tissue loading becomes very important. The important need in orthopaedics field is to develop a model without too much simplification. In this thesis for the first time the complete computational model of hip with soft tissue has been used to detect the impingement in a specific patient. The effect of centre of rotation and soft tissue are considered on impingement detection. In this study the femur, acetabulum, cartilage and ligaments of specific patients were modelled in MIMICs (Materialise' Interactive Medical Image Control System) using both MRI and CT scan. 3D hip models with and without soft tissues of normal hip, hip with impingement and hip with impingement after reshaping were modelled. The hip models were meshed in 3-Matic. The hip models were imported to Abaqus and boundary conditions were applied. Impingement zone and impingement angle was detected in Abaqus. Different centre of rotation was applied to consider the effect of centre of rotation to detect impingement. Experimental studies were set up to validate the hip models. Mocap, Wiimote, MotionNode and goniometer were used together at the same time to measure the flexion, adduction and internal rotation in 90⁰ of flexion in twenty two healthy volunteers. Validity and reliability of all of the methods were calculated. It is the first time that reliability and validity of Wiimote and MotionNode are considered to be used in medical application. Our results show that the model with soft tissue is closer to the experimental results. It shows that the soft tissue in hip model affects hip impingement angle and hip biomechanics. This finding also shows that, if the boundary condition is closer to the real hip, then the results of computer-aided program will be more reliable.

abstract: This thesis aims to explore the language of different bodies in the field of dance by analyzing the habitual patterns of dancers from different backgrounds and vernaculars. Contextually, the term habitual patterns is defined as the postures or poses that tend to re-appear, often unintentionally, as the dancer performs improvisational dance. The focus lies in exposing the movement vocabulary of a dancer to reveal his/her unique fingerprint. The proposed approach for uncovering these movement patterns is to use a clustering technique; mainly k-means. In addition to a static method of analysis, this paper uses an online method of clustering using a streaming variant of k-means that integrates into the flow of components that can be used in a real-time interactive dance performance. The computational system is trained by the dancer to discover identifying patterns and therefore it enables a feedback loop resulting in a rich exchange between dancer and machine. This can help break a dancer’s tendency to create similar postures, explore larger kinespheric space and invent movement beyond their current capabilities. This paper describes a project that distinguishes itself in that it uses a custom database that is curated for the purpose of highlighting the similarities and differences between various movement forms. It puts particular emphasis on the process of choosing source movement qualitatively, before the technological capture process begins. / Dissertation/Thesis / Masters Thesis Computer Science 2016

Cette thèse porte sur le traitement de données multi-capteurs liées à la locomotion humaine.Son objectif est de concevoir des outils pour la segmentation de la locomotion à partir d'un réseau de capteurs embarqués et appliquée à deux domaines différents: le sport avec l'ultra-marathon et la déficience causée par un symptome de la maladie de Parkinson. Pour ces deux applications, le travail peut atteindre cet objectif concerné. d'une part, les contraintes matérielles liées au réseau de capteurs, et d'autre part, les algorithmes de traitement des données. Dans un premier temps, nous avons recueilli des données multi-capteurs sur un coureur du Marathon des Sables. Le réseau des capteurs étant confronté à des conditions extrêmes, il a fallu s'adapter à des problèmes techniques avant de pouvoir proposer un outil pour segmenter et classer ces grandes quantités de données. Dans un second temps, nous avons travaillé en collaboration avec un médecin, pour comprendre au mieux le ''freezing" (symptôme perturbant la marche de certains malades atteints de la maladie de Parkinson) afin de proposer une nouvelle méthode de détection pour ce symptôme. / This thesis focuses on the treatment of multi-sensor related data locomotion humaine.Son goal is to develop tools for segmentation of locomotion from a network of embedded and applied to two different domains sensors : sport with ultra -marathon and disability caused by a symptom of Parkinson's disease . For both applications, the work can achieve this question. one hand , the physical constraints of the network sensors , and secondly , the data processing algorithms . At first , we collected multi-sensor data on a runner Marathon des Sables. The network of sensors being confronted with extreme conditions, it was necessary to adapt to technical before proposing a tool to segment and classify these large amounts of data problems. In a second step , we worked with a doctor, to understand better the '' freezing " (symptom disrupting the progress of some patients with Parkinson's disease ) to propose a new detection method for this symptom.

Conselho Nacional de Desenvolvimento Científico e Tecnológico / O objetivo do presente trabalho foi avaliar comparativamente parâmetros biomecânicos (tanto antropométricos, quanto cinemáticos) de dados obtidos a partir do console Microsoft Kinect (2010). A avaliação destes parâmetros foi realizada para validar seu uso para obter informações complementares à Análise Ergonomica do Trabalho (AET) e em outras pesquisas, cujos objetivos envolvem o diagnóstico de uso de produtos ou ambientes de trabalho a partir da análises posturais e interações da população que o utiliza. A pesquisa com este console em particular é justificada uma vez que seu lançamento modificou o cenário da biomecânica, já que se trata de um equipamento acessível e portátil. Porém, sua precisão em relação à outros equipamentos ainda está em aberto, sendo inclusive, objeto de estudo de muitas pesquisas em andamento. Os dados obtidos por meio de sistemas de captura de movimentos tridimensionais permitem a avaliação de produtos, atividades e análises de interações homem-objeto. No campo do Design, é uma importante realização, uma vez que permite que profissionais tenham acesso à ferramenta que, anteriormente, era limitada à nichos especializados. O console foi comparado com o sistema de captura de movimentos inercial MVN Biomech (XSENS TECHNOLOGIES) e com o tradicional registro por meio de vídeo. Para obter dados do console Kinect, um software disponível no mercado foi selecionado a partir de critérios predefinidos para obter dados cinemáticos do console. Dois experimentos laboratoriais foram realizados: o primeiro, teve como objetivo obter dados operacionais dos equipamentos e suas limitações de uso; e o segundo foi realizado de forma a obter dados biomecânicos e compará-los a partir de três parâmetros estáticos e um dinâmico. Os parâmetros estáticos envolveram ângulos articulares e segmentares em posturas selecionadas e dimensões segmentares, onde a proposta foi avaliar dados antropométricos e as características do modelo biomecânico referente à manter os corpos rígidos durante a movimentação. O parâmetro dinâmico foi realizado de forma a obter dados de deslocamento global das articulações em movimentações selecionadas. Para possibilitar esta análise, uma plataforma digital foi desenvolvida, constituindo um campo neutro para o tratamento dos dados. A plataforma mantém os dados originais dos sistemas, permitindo a distinção entre os modelos biomecânicos e a retirada de dados que possam ser comparados. Os experimentos realizados permitiram avaliar a usabilidade do console, fornecendo diretrizes para seu uso. Para avaliar a utilização do console em ambientes reais de trabalho, foram realizados registros preliminares em laboratórios químicos, os quais se mostraram viáveis se as limitações, semelhantes às de sistemas baseados em tecnologia ótica, sejam consideradas. Futuras análises devem ser conduzidas para validar estatisticamente os resultados obtidos. Porém, considerando o objetivo do trabalho, pode-se concluir que o sistema avaliado é uma alternativa confiável no contexto proposto. / The aim of the present study was to evaluate biomechanical parameters (both, anthropometric and kinematic) from data acquired through Microsoft Kinect (2010). The validation of its biomechanical characteristics will allow its use in gathering information to complement Ergonomic Work Analysis (EWA) and other user researches that provide product and work environment diagnosis through postural and dynamic assessment. The use of MS Kinect in this research is justified by the fact that is it has changed biomechanical scenario due to the fact that it is an inexpensive and portable alternative to the available motion capture systems available in the market. However, its accuracy has been the subject of many ongoing researches Data acquired from 3D motion capture systems provide means for evaluating products, activities and human-object interactions. In Design, its an important achievement, since it allows professionals to use the tool, considering that most motion capture systems available in the market are not accessible. The Microsoft console was compared to MVN Biomech inertial system (XSENS TECHNOLOGIES) and traditional 2D video data. In order to acquire kinematic data form MS Kinect, a software was chosen, following a few criteria. Two laboratorial experiments were held, where the first aimed to acquire operational details and limitations from the equipments, as for the second aimed to compare biomechanical data through three static parameters and one dynamic. The static parameters involved joint and segment angles, as well as a segments dimensional comparison, whereas the proposals were to assess anthropometric features and to understand if the biomechanical model considers the segments as rigid bodies. The dynamic comparison was based on joints global displacement in selected movements. In order to analyze data from different systems, a digital platform based on a game engine was developed, constituting an even ground for evaluation. The platform maintains original data from the biomechanical models and extracts kinematic parameters, which can be compared. The experiments have provided understanding on the consoles operations, providing guidelines for its usage. In order to also evaluate its usage in real work environments, trial recordings were held in chemical laboratories. These trials have shown the alternative to be viable if the limitations, similar to optical systems, are considered. Future analyses should be conducted in order to statistically validate the results. However, given the goals and context of this research, it can be concluded that the evaluated system is a reliable motion capture alternative.

Rörelseigenkänning (motion capture) med optiska mätsystem används i flera applikationer för översättning av positioner i det fysiska rummet till det virtuella. I det här arbetet approximeras den snittvolym som motsvarar vad två eller fler kameror ser i ett sådant optiskt mätsystem. Volymen approximeras med en octree-datastruktur som lagrar information om kvalitet för individuella delar i volymen. Datastrukturens associerade kvalitetsmått används i kombination med ett vinkelmått i ett senare delsteg för att optimera fram en kamerauppsättning med en genetisk algoritm. Volymapproximeringens konstruktion implementerades i C++ och den genetiska algoritmen använder specialiserad överkorsning och initiering. Genomet är utformat så att problemdomänen begränsas till det aktuella problemet. Resultatet av optimeringen visar att vidareutveckling är nödvändig och lösningarna som optimerats fram var inte tillräckliga. Potentiella framtida arbeten innefattar fortsatt utveckling av nuvarande kvalitetsmått, samt vidare jämförande studier av volymapproximeringen.

Denna studie presenterar en artefakt som med hjälp av Microsoft Kinect, samlar in och beräknar biomekanisk data från golfsvingar för att identifiera nyckelpositioner på ett automatiserat sätt. Den övergripande metoden som används är design-science research. Kinect sensorn är egentligen gjord för tv-spel, men kan även användas allmänt för att fånga och samla in kvantitativ biomekanisk data. Sensorn är inte specifikt utformad för golfsvingar, och saknar dessutom förmågan att spåra externa objekt som golfklubbor. Dessa problem var grunden för denna studies övergripande syfte, nämligen att utveckla en mjukvara med förmågan att identifiera de fem viktigaste nyckelpositionerna i golfsvingen. Nyckelpositionerna definieras utifrån mätbara egenskaper vilket för nyckelpositionen impact, krävde att man utnyttjade sensorns förmåga att spela in ljud. I empirin som genomfördes på en driving range samlades data från sammanlagt 20 svingar in. Varje identifierad nyckelposition analyserades på ett kvalitativt sätt utifrån ett antal sammanställda kriterier. Kinectsensorn hade problem att identifiera vissa positioner, men sammantaget bedömdes 87 % av de insamlade nyckelpositionerna som korrekt identifierade. För nyckelpositionen impact, där insamlad ljuddata användes för identifiering, bedömdes 85 % av de insamlade nyckelpositionerna som korrekt identifierade. Studien begränsar sig till utvalda nyckelpositioner men visar potential för automatiserad insamling av kvalitativ golfsvingdata, och ger uppenbara möjligheter för vidare forskning. / This study presents an artifact that is using Microsoft Kinect for motion capturing of golf swings, in order to identify key positions in an automatic fashion. The main method used is design science research. The Kinect sensor, which is developed for the Xbox video game console, can be used for general motion capture. It is, however, not tailored for golf swings and it also lacks the ability to track external objects such as the golf club. These problems were the main motivation for the purpose of this study, i.e. to develop an application to identify the five most important positions in the golf swing. The key positions were defined based on measurable traits, making it necessary to use the audio recording ability of the sensor for the impact position. The empirical investigation was performed at a driving range, and data from a total of 20 golf swings were gathered. In the next step, every key position was analyzed in a quantitative manner based on a number of criteria. The results show that the Kinect sensor may have some troubles recognizing certain positions, but still 87 % of the key positions captured were considered to be successfully identified. Specifically, 85 % of all impact positions were successfully identified. The study was limited to the chosen key positions, but shows good potential for automatic capturing of quantitative golf swing data, thus suggesting several possible directions for future research.

This thesis was carried out at Imagination Studios in Uppsala. IMS is a motion capture studio that alsodoes animation. Motion capture is the capturing of (generally) human motions to make 3Danimations look more realistic. In motion capture, the actors have to imagine the scene. The goal ofthis thesis is to help the motion capture actor by creating a tool that lets the actor interact with avirtual agent that represents his acting partner. Scenarios and a video sketch were created todescribe how the interaction can work. The Microsoft Kinect is used to capture the motions of theactor and recognize gestures. These gestures are then responded to by a virtual agent that isdisplayed in a 3D environment created in the Unreal Development Kit. Programming was done in C++and UnrealScript to make this solution work. Motions were recorded and applied to the virtual agentto create realistic animations that are played in response to the actor's gestures. The final product isan interactive application that can be used to immerse a person in an acting scenario.