This thesis presents a markerless multiple-camera vision-based 30 human tracking method for industrial environments. The method can track humans in the vicinity of moving robots without using skin color cues or articulated human models. It is robust to self-occlusions and to partial occlusions caused by the robot. Foreground pixels corresponding to humans are found by background subtraction. A convex polyhedron enclosing the human(s) is generated online by bounding the foreground pixels in 30 space. Experimental results are included for a single person and multiple persons walking near a moving PUMA robot in a cluttered environment. Reliable tracking at 11.2Hz is demonstrated using four cameras and a Pentium 4 PC. The tracking data may be used for online robot collision avoidance. / Thesis / Master of Applied Science (MASc)

Abstract Background: Osteoarthritis (OA) is a prevalent joint disease causing significant disability, particularly in the knee often treated end-stage with joint replacement surgery. While partial knee arthroplasty (PKA) is noted for quicker recovery and better functionality compared to total knee arthroplasty (TKA), its underutilization highlights a gap in surgical decision-making, driven by a lack of objective data on pre-operative functional differences. Methods: This prospective observational study, conducted from November 2023 to April 2024 at St. Joseph’s Healthcare Hamilton, included 34 end-stage OA patients scheduled for knee arthroplasty. Participants underwent pre-operative functional assessments using markerless motion capture technology to analyze gait and mobility during walking and sit-to-stand tests. Results: The study found no significant differences in basic gait and sit-to-stand metrics between the PKA and TKA groups at a preferred pace. However, at a faster pace, PKA patients demonstrated greater adaptability, showing significant increases in peak stance knee flexion, knee flexion excursions, and stride length, compared to TKA patients whose gait patterns remained consistent across speeds. Conclusion: PKA patients exhibit greater functional adaptability in their pre-operative state, suggesting potential underestimation of their capabilities in current surgical evaluations. Incorporating varied-pace walking tests in pre-operative assessments may provide deeper insights into functional capabilities, influencing more tailored surgical decisions and potentially increasing the application of PKA in suitable candidates. / Thesis / Master of Applied Science (MASc)

Respiration introduces large tumor motion in the thoracic region which influences treatment outcome for lung cancer patients. Tumor motion management techniques require characterization of temporal tumor motions because tumor motion varies patient to patient, day to day and cycle to cycle. This work develops a markerless algorithm to estimate 3 dimensional (3D) lung-tumor trajectories on free breathing cone beam computed tomography (CBCT) projections, which are 2 dimensional (2D) sequential images rotating about an axis and are used to reconstruct 3D CBCT images. A gold standard tumor trajectory is required to guide the algorithm development and estimate the tumor detection accuracy for markerless tracking algorithms. However, a sufficient strategy to validate markerless tracking algorithms is lacking. A validation framework is developed based on fiducial markers. Markers are segmented and marker trajectories are xiv obtained. The displacement of the tumor to the marker is calculated and added to the segmented marker trajectory to generate reference tumor trajectory. Markerless tumor trajectory estimation (MLTM) algorithm is developed and improved to acquire tumor trajectory with clinical acceptable accuracy for locally advanced lung tumors. The development is separate into two parts. The first part considers none tumor deformation. It investigates shape and appearance of the template, moreover, a constraint method is introduced to narrow down the template matching searching region for more precise matching results. The second part is to accommodate tumor deformation near the end of the treatment. The accuracy of MLTM is calculated and compared against 4D CBCT, which is the current standard of care. In summary, a validation framework based on fiducial markers is successfully built. MLTM is successfully developed with or without the consideration of tumor deformation with promising accuracy. MLTM outperforms 4D CBCT in temporal tumor trajectory estimation.

Joint kinematics of upper extremity (UE) impairments in a pediatric population are often difficult to examine using marker-based motion capture. As a result of the cost and availability of tools such as marker-based motion capture in clinical settings, clinicians use functional tasks to examine improvement in movement quality. However, some of these tasks, such as the Box and Block test (BBT), which is examined in this study, rely on scoring to assess motor improvement. This scoring method can be misleading due to the possibility of movement compensation to improve scores. Therefore, finding kinematic correlations that can lead to improved BBT scores could improve the quality of functional assessments by providing discrete measures for clinicians. Understanding human motion using marker-based motion capture has been the accepted standard in biomechanics. However, it is not without its drawbacks, especially in upper extremity examination due to complex anatomical positioning. The introduction of markerless motion capture software could drastically alter how human biomechanics is analyzed in various settings. Additionally, avoiding possible errors due to clothing and skin movement could greatly improve reported results. Therefore, examining similarities in UE joint kinematics between accepted marker-based and markerless software could introduce markerless motion capture as a method for examining complex kinematics. This study aims to examine UE joint kinematics in a typically developing pediatric population while they complete the BBT, as well as validate Theia3D (Theia Markerless Inc., Kingston, ON, Canada). Marker-based motion capture was used to capture UE kinematics during the BBT. This study was performed on typically developing children aged 7, 9, and 11. Average and peak joint angles were determined, as well as hand segment velocity and path length. Significant correlations to BBT scores were found in peak shoulder flexion (FLEX) angle (r = -0.556, p-value = 0.009), peak (r = -0.479, p-value = 0.028), and average (ρ = -0.535, p-value = 0.012) wrist extension (EXT) angle, average mediolateral (ML) hand segment velocity (r = 0.494, p-value = 0.023), and path length (r = -0.522, p-value = 0.015). Additionally, significant differences between BBT scores (p-value = 0.005), peak shoulder FLEX (p-value = 0.024), and peak shoulder abduction (ABD) angle (p-value = 0.022) were found between the 7- and 11-year-old age groups. Peak elbow FLEX angle was significantly different (p-value = 0.049) between 9- and 11-year-old age groups. These results show that the BBT score could be related to the shoulder and wrist angle, as well as hand segment velocity and path length for typically developing children. Furthermore, root mean square deviation (RMSD) values less than 6° existed in all joint angles. Intraclass correlation coefficients (ICCs) greater than 0.75 were found in shoulder ABD (ICC = 0.79), forearm pronation (ICC = 0.81), wrist EXT (ICC = 0.75), and radial deviation (ICC = 0.87). Additionally, validation results between the marker-based and markerless systems show that there are differences in pose estimations and joint calculations based on rotation sequences. Overall, UE joint kinematics are shown to have correlations to BBT scores, so scores alone may not be indicative of movement quality in other patient populations. Markerless motion capture shows many benefits, however, it should be noted that, due to the complexity of upper extremity motion analysis, understanding what joint rotation sequences align the best with task-specific motions is important. / Master of Science / Human motion is commonly analyzed using marker-based motion capture, which consists of fitting participants with retroreflective markers that can be seen by specialized cameras. However, due to equipment costs, difficult implementation, and the occurrence of markers shifting on skin or being concealed by clothing, markerless motion capture is beginning to be introduced into biomechanics research and could be used in hospitals, clinical settings, and for outdoor examination due to its versatility. The software uses machine learning software that can determine skin landmarks in videos from several cameras to develop a 3D skeleton. Markerless motion capture could be beneficial in examining patients with neuromotor disorders or injuries due to being able to capture abnormal or quick movement which often accompanies many neurological disorders that affect motor function. Additionally, observing movement in children is a challenge due to markers being too close together on smaller limbs. Due to cost and obtainability, clinicians tend to use functional tests to examine improvements in motor function by a scoring system relevant to the specific test, such as the Box and Block test (BBT) which will be used in this study. However, there is the possibility of the patient's ability to adapt to the test to improve their score without improving general motor function. Therefore, it is important to find a relationship between upper limb movement and BBT scores. This study aims to find correlations between upper limb movement and Box and Block test scores as well as differences between 7-, 9-, and 11-year-old age groups and compare marker-based motion capture and the Theia3D (Theia Markerless Inc., Kingston, ON, Canada) markerless motion capture software. Joint assessment is completed with motion capture, which uses reflective markers on specific landmarks on the skin surface. Markerless motion capture is collected simultaneously with marker-based motion capture to assess similarities. The entire procedure was also completed 2 times within 1 visit. The results showed meaningful comparisons between the BBT scores and shoulder and wrist angle, and hand velocity. BBT scores and shoulder angles were shown to be different between the 7- and 11-year-old age groups. Elbow angles were shown to be different between the 9- and 11-year-old age groups. Additionally, comparisons between the marker-based and markerless results showed that all resulting joint angle data captured by each system were similar. Markerless measurement comparisons showed similarities between both sessions as well. These results show that there are ways to provide discrete measurements in clinical settings to examine movement quality. Comparisons between both motion analysis systems show the need to determine task-specific analyses to obtain meaningful results concerning the upper limbs, due to the inherent joint complexity and differing methods of completing the same task.

Hand and finger movements are underrepresented in biomechanical studies, primarily due to the challenge of tracking the hands and fingers. Several limitations are associated with marker-based motion capture, including interference with natural movement, and require the tedious, time-consuming application of numerous markers. Advancements in computer vision have led to the development of markerless motion capture systems yet validation of markerless systems for the upper extremities is limited, especially the hand and fingers. The purpose of this study was to develop and assess a markerless motion capture system capable of tracking hand and finger kinematics. A markerless system using four synchronized webcams was developed. Camera pairs were organized in different angles Centre90° (C/90°), Left45°/Right45° (L45°/R45°), and Centre/Left45° (C/L45°). Motion capture was performed with both marker-based and markerless systems. Twenty healthy participants performed five dynamic hand tasks with and without markers. Three-dimensional joint positions were defined using a musculoskeletal model in OpenSim. No significant differences were observed between C/90° and C/L45° markerless camera pairs and the marker-based system. The L45°/R45° camera pair differed significantly from other markerless pairs in several tasks but agreed with the marker-based system for the index finger during flexion. For most of the fingers, no significant differences were found across the different camera pairs. Correlations and error for the concurrent finger flexion task revealed high consistency among all the camera pairs, with R² above 0.90 and RMSD below 10°, the thumb showed greater variability. The R² and RMSD varied depending on the camera comparison and finger for each task. Markerless motion capture for the hands and fingers is possible with little difference to marker-based systems and is dependent on the camera orientation used. / Thesis / Master of Science in Kinesiology

C. difficile is an obligate anaerobic, Gram-positive, rodshaped and spore-forming bacterium. It is a well-recognised causative agent of antibiotic-associated diarrhoea and pseudomembranous colitis. C. difficile has emerged as an important nosocomial pathogen in recent years, associated with considerable morbidity, mortality and economic burden. Despite its importance, functional genomic studies have been lagging behind in comparison to other enteric pathogens. This is attributed to the fact that C. difficile is difficult to manipulate genetically and the lack of robust, reproducible mutagenesis systems for many years. The ideal mutation for robust functional genomic studies is a markerless, in-frame deletion of the gene of interest. All systems developed for C. difficile, up to the start of this study, involve insertional inactivation of the gene of interest. This study describes the development of a novel genetic system for C. difficile, to create precise and markerless chromosomal deletions, using the meganuclease ISceI. For validation of the system, the addBA genes in C. difficile were deleted. The AddAB enzyme complex is important in the survival of many bacteria, since it maintains genome integrity, by the repair of double-strand breaks. Deletion of addBA in C. difficile did not significantly affect growth and viability, but the mutant strains were sensitive to DNA damaging agents. In addition, it was shown that C. difficile is capable of initiating the SOS response after DNA damage and that AddAB is not necessary for the induction of this response. The genetic system was further optimised to delete type IV pili (TFP)- associated genes, particularly pilT (CD3505) and pilA (CD3507), to investigate twitching motility. TFP are important in virulence and pathogenesis of many bacteria and twitching motility is often involved. TFP in C. difficile may be expressed in vivo during infection and may be involved in biofilm formation and colonization. To study potential TFP-mediated motility, a non-flagellated C. difficile strain was first constructed by deleting the fliC gene. The pilT gene, predicted to encode a protein involved in TFP retraction, was then deleted in the ΔfliC strain. A ΔpilT strain was also generated. Preliminary experimental work using these strains did not show any evidence for twitching motility and no difference between the ΔpilT strains and the parental strains. Examination of cells from the ΔfliC strain, under various conditions, did not reveal any pili, which indicates that TFP are regulated in C. difficile and that the TFP locus might be repressed at the transcriptional level. Preliminary work to investigate an intergenic region located upstream of the TFP locus in C. difficile, that might be involved in regulation, suggested that transcription is being initiated within a 500 bp region upstream of the CD3513 gene.

This thesis presents a study on how to create a production pipeline using a markerless motion capture system for the creation of animations in computer games. The questions the authors desire to answer are: Is it possible to create a pipeline that uses markerless motion capture for the creation of animations in computer games? And also: Can a markerless motion capture system fit in an animation pipeline for games? This thesis is based on previous work by Kakee Lau (Lau, 2012), a former student of Gotland University College. He describes a pipeline for working with passive optical motion capture for games. To fit the markerless motion capture system, there must be some changes to Lau’s already established pipeline. The method used in this thesis is based on a pipeline described in Lau’s thesis (Lau, 2012). The authors have made some alterations to this pipeline for it to be more suitable for markerless motion capture. The pipeline that the authors propose covers the setup of two Kinect cameras, the calibration, the recording, the cleaning and the preparation for MotionBuilder. Due to some factors that were not taken into consideration during testing, there cannot be any quantitative conclusion in this thesis to which system is the better one. Based on the findings of this study the authors can conclude that a markerless motion capture system is a viable method for game animation creation, yet not giving the same quality of results as a passive optical motion capture system.

Made available in DSpace on 2014-06-12T15:53:49Z (GMT). No. of bitstreams: 2 arquivo1931_1.pdf: 3171518 bytes, checksum: 18e05da39f750dea38eaa754f1aa4735 (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2009 / Atualmente, com o aumento do poder computacional e os estudos em usabilidade, sistemas de tempo real e foto-realismo, os requisitos de qualquer sistema de computador são mais complexos e sofisticados. Sistemas de Realidade Aumentada não são exceção em sua tentativa de resolver problemas da vida real do usuário com um nível reduzido de risco, tempo gasto ou complexidade de aprendizado. Tais sistemas podem ser classificados como baseados em marcadores ou livres de marcadores. O papel essencial da realidade aumentada sem marcadores é evitar o uso desnecessário e indesejável de marcadores nas aplicações. Para atender à demanda por tecnologias de realidade aumentada robustas e não-intrusivas, esta dissertação propõe uma cadeia de execução para o desenvolvimento de aplicações de realidade aumentada sem marcadores, especialmente baseadas na técnica de recuperação da estrutura a partir do movimento em tempo real

京都大学 / 新制・課程博士 / 博士(人間健康科学) / 甲第24542号 / 人健博第113号 / 新制||人健||8(附属図書館) / 京都大学大学院医学研究科人間健康科学系専攻 / (主査)教授 中尾 恵, 教授 杉本 直三, 教授 黒田 知宏 / 学位規則第4条第1項該当 / Doctor of Human Health Sciences / Kyoto University / DFAM

Modern soldiers are burdened by an increase in body-borne load due to technological advancements related to their armour and equipment. Despite the potential increase in safety from carrying more protective equipment, a heavier load on the soldier might decrease field performance both cognitively and physically. Additionally, an increasing load on military personnel concurrently increases their risk of musculoskeletal injuries. Therefore, there is a necessity for research on the soldier's biomechanical outcomes under different loading conditions. When it comes to biomechanics research, marker-based technology is widely accepted as the gold standard in terms of motion capture. However, recent advancements in markerless motion capture could allow the quick collection of data in various training environments, while avoiding marker errors. In this research project, the Theia3D markerless motion capture system was compared to the marker-based gold standard for application on participants across varying body-borne load conditions. The aim was to estimate lower body joint kinematics, gastrocnemius lateralis and medialis muscle activation patterns, and lower body joint reaction forces from the two motion capture systems. Data were collected on 16 participants for three repetitions of both walking and running under four body-borne load conditions by both motion capture systems simultaneously. Electromyography (EMG) data of lower limb muscles were collected on the right leg and force plates measured ground reaction forces. A complete musculoskeletal analysis was completed in OpenSim using the Rajagopal full-body model and standard workflow: model scaling, inverse kinematics, residual reduction, static optimization, and joint reaction analysis. Estimations of joint kinematics and joint reaction forces were compared between the two systems using Pearson's correlation coefficient, root-mean-square errors, and Bland-Altman limits of agreement. Very strong correlations (r = 0.960 ± 0.038) and acceptable differences (RMSE = 7.8° ± 2.6°) were observed between the kinematics of the marker-based and markerless systems, with some angle biases due to joint centre differences between systems causing an offset. Because the marker-based motion capture system lost line of sight with markers more frequently in the heavier body-borne load conditions, differences generally increased with heavier body-borne loads. Timing of muscle activations of the gastrocnemius lateralis and medialis as estimated from both systems agreed with the ones measured by the EMG sensors. Joint reaction force results also showed a very strong correlation between the systems but the markerless model seemed to overestimate joint reaction forces when compared to results from the marker-based model. Overall, this research highlighted the potential of markerless motion capture to track participants across all body-borne load conditions. However, more work is necessary on the determination of angle bias between the two systems to improve the use of markerless data with OpenSim models.