Magnetic interference in the motion capture environment is caused primarily by ferromagnetic objects and current-carrying devices disturbing the ambient, geomagnetic field. Inertial sensors gather magnetic data to determine and stabilize their global heading estimates, and such magnetic field disturbances alter heading estimates. This decreases orientation accuracy and therefore decreases motion capture accuracy. The often used Kalman Filter approach deals with magnetic interference by ignoring the magnetic data during periods interference is encountered, but this method is only effective when the disturbances are ephemeral, and cannot not retroactively repair data from disturbed time periods. The objective of this research is to develop a method of magnetic interference mitigation for environments where magnetic interference is the norm rather than the exception. To the knowledge of this author, the ability to use inertial and magnetic sensors to capture accurate, global, and drift-free orientation data in magnetically disturbed areas has yet to be developed. Furthermore there are no methods known to this author that are able to use data from undisturbed time periods to retroactively repair data from disturbed time periods. The investigation begins by exploring the use of magnetic shielding, with the reasoning that application of shielding so as to impede disturbed fields from affecting the inertial sensors would increase orientation accuracy. It was concluded that while shielding can mitigate the effect of magnetic interference, its application requires a tedious trial and error testing that was not guaranteed to improve results. Furthermore, shielding works by redirecting magnetic field lines, increasing field complexity, and thus has a high potential to exacerbate magnetic interference. Shielding was determined to be an impractical approach, and development of a magnetic inference mitigation algorithm began. The algorithm was constructed such that magnetic data would be filtered before inclusion in the orientation estimate, with the result that exposure in an undisturbed environment would improve estimation, but exposure to a disturbed environment would have no effect. The algorithm was designed for post-processing, rather than real-time use as Kalman Filters are, which enabled magnetic data gathered before and after a time point could affect estimation. The algorithm was evaluated by comparing it with the Kalman Filter approach of the company XSENS, using the gold standard of optical motion capture as the reference point. Under the tested conditions of stationary periods and smooth planar motion, the developed algorithm was resistant to magnetic interference for the duration of testing, while the Kalman Filter began to degrade after approximately 15 seconds. In a 190 second test, of which 180 were spent in a disturbed environment, the developed algorithm resulted in 0.4 degrees of absolute error, compared to the of the Kalman Filter’s 78.8 degrees. The developed algorithm shows the potential for inertial systems to be used effectively in situations of consistent magnetic interference. As the benefits of inertial motion capture make it a more attractive option than optical motion capture, immunity to magnetic interference significantly expands the usable range of motion capture environments. Such expansion would be beneficial for motion capture studies as a whole, allowing for the cheaper, more practical inertial approach to motion capture to supplant the more expensive and time consuming optimal option.

ABSTRACT. This research is following Ecological Theory about the ability of humans to form impressions from observing the behavior of other people. The current study examined whether personality traits were related to the way in which people walked and moved to certain music. Twenty-one young females were asked to walk and to move to slow and fast music and to dance with a partner. Their movements were tracked with a MOCAP system which can produce coordinates of points on a moving body. A number of different measurements of body movement were produced and analyzed. Participants also completed the Big Five personality inventory. A number of trends were found in relationships between personality traits and gait and dance movement. Extroversion had the biggest influence. It was related to bigger and faster movements, especially with movements of head, hands, shoulders, hips or footstep. Openness to experience tended to have similar influence as extroversion. Neuroticism influenced slow dance the most. Agreeableness and conscientiousness had both positive and negative influence to a lesser extent. They influenced especially movements of hands, hips or footstep.

Motion Capture is a prevalent and useful technology in the animation industry as well as the medical and military industries. As technology becomes better and cheaper it begins to enter the consumer market. A consumer interest in motion capture animations made by anyone has been created with the technology. This paper will focus on a review of the new technologies that have allowed the beginning of consumer-level motion-capture animations. Included will be a review of the history of motion capture and then a study of methods, workflows, and necessary prerequisites for making motion capture data using consumer-available tools. The study involves reviewing how easy each method is to understand and how usable the data made is for use in animations.

X-ray computed tomography (CT) is a popular imaging technique used for reconstructing volumetric properties for a large range of objects. Compared to traditional optical means, CT is a valuable tool for analyzing objects with interesting internal structure or complex geometries that are not accessible with. In this thesis, a variety of applications in computer vision and graphics of inverse problems using tomographic imaging modalities will be presented: The first application focuses on the CT reconstruction with a specific emphasis on recovering thin 1D and 2D manifolds embedded in 3D volumes. To reconstruct such structures at resolutions below the Nyquist limit of the CT image sensor, we devise a new 3D structure tensor prior, which can be incorporated as a regularizer into more traditional proximal optimization methods for CT reconstruction. The second application is about space-time tomography: Through a combination of a new CT image acquisition strategy, a space-time tomographic image formation model, and an alternating, multi-scale solver, we achieve a general approach that can be used to analyze a wide range of dynamic phenomena. Base on the second application, the third one is aiming to improve the tomographic reconstruction of time-varying geometries undergoing faster, non-periodic deformations, by a warp-and-project strategy. Finally, with a physically plausible divergence-free prior for motion estimation, as well as a novel view synthesis technique, we present applications to dynamic fluid imaging (e.g., 4D soot imaging of a combustion process, a mixing fluid process, a fuel injection process, and view synthesis for visible light tomography), which further demonstrates the flexibility of our optimization framework.

This paper deals with techniques for acquiring data for character animation driven from video. Among other, it also presents several Motion Capture systems and animation data formats BVH and CSM. It also contains an example application demonstrating attained accomplishments. These are reviewed and there is instituted a course of future proceeding.

京都大学 / 0048 / 新制・課程博士 / 博士(人間・環境学) / 甲第19793号 / 人博第764号 / 新制||人||184(附属図書館) / 27||人博||764(吉田南総合図書館) / 32829 / 京都大学大学院人間・環境学研究科共生人間学専攻 / (主査)教授 神﨑 素樹, 教授 森谷 敏夫, 教授 石原 昭彦 / 学位規則第4条第1項該当 / Doctor of Human and Environmental Studies / Kyoto University / DFAM

3D modelling is a technology in massive demand now and can potentially become a key factor for enabling subsequent technological evolutions such as metaverses, digital twins, and virtual reality. Current 3D modellings include high-precision 3D human body modelling and rapid modelling through single or multiple monocular photos. However, some problems persist in both modellings. The modelling based on high-precision equipment has low practicability, few applicable scenarios, and high cost. Modelling through monocular photos, on the other hand, has low accuracy and is sensitive to noisy data. And both modellings generate static 3D models. Therefore, to realize the model's dynamic effect in various fields while retaining fast modelling, we propose a system that recovers a 3D model from a single photo to fuse skeleton animation extracted from videos, for a realization of the Digital Twin (DT). DT is defined as "digital replications of living as well as non-living entities that enable data to be seamlessly transmitted between the physical and virtual worlds". Rigging is setting up the skeleton-based animation to combine the 3D model and skeleton animation. Traditional rigging method is time-consuming and non-reusable, since rigging is often done manually or semi-automatically. In this thesis, we propose an automatic rigging method to achieve a loose coupling fusion of one-to-many or many-to-one 3D models and skeletal animations. Our rigging method is fast and efficient, and only needs a single photo as input.

Ever since the first use of crowds in films and videogames there has been an interest in larger, more efficient and more realistic simulations of crowds. Most crowd simulation algorithms are able to satisfy the viewer from a distance but when inspected from close up the flaws in the individual agent's movements become noticeable. One of the bigger challenges faced in crowd simulation is finding a solution that models the actual movement of an individual in a crowd. This paper simulates a more realistic crowd by using individual motion capture data as well as traditional crowd control techniques to reach an agent's desired goal. By augmenting traditional crowd control algorithms with the use of motion capture data for individual agents, we can simulate crowds that mimic more realistic crowd motion, while maintaining real-time simulation speed.

A novel anatomical behavioral descriptive taxonomy improves motion capture in complex motor stereotypies (CMS) by indexing precise time data without degradation in the complexity of whole body movement in CMS. The absence of etiological explanation of complex motor stereotypies warrants the aggregation of a core CMS dataset to compare regulation of repetitive behaviors in the time domain. A set of visual formalisms trap configurations of behavioral markers (lateralized movements) for behavioral phenotype discovery as paired transitions (from, to) and asymmetries within repetitive restrictive behaviors. This translational project integrates NIH MeSH (medical subject headings) taxonomy with direct biological interface (wearable sensors and nanoscience in vitro assays) to design the architecture for exploratory diagnostic instruments. Motion capture technology when calibrated to multi-resolution indexing system (MeSH based) quantifies potential diagnostic criteria for comparing severity of CMS within behavioral plasticity and switching (sustained repetition or cyclic repetition) time-signatures. Diagnostic instruments sensitive to high behavioral resolution promote measurement to maximize behavioral activity while minimizing biological uncertainty. A novel protocol advances CMS research through instruments with recursive design.

No / In this paper we present a constrained inverse kinematics algorithm for real-time motion capture in virtual environments, that has its origins in the simulation of multi-body systems. We apply this algorithm to an articulated human skeletal model using an electromagnetic motion tracking system with a small number of sensors to create avatar postures. The method offers efficient inverse kinematics computation and it is also generalised for the configurations of an articulated skeletal model. We investigate the possibility of capturing fast gestures by analysing the convergence patterns of the algorithm with the motion tracking sampling frequency for a range of actions.