Thesis (Ph.D.) - University of Queensland, 2006. / Includes bibliography.

Thesis (M.S.)--Ohio State University, 1985. / Includes bibliographical references (leaves 101-103). Available online via OhioLINK's ETD Center

The creation of anatomically correct three-dimensional joints for the simulation of humans is a complex process, a key difficulty being the correction of invalid joint configurations to the nearest valid alternative. Personalised models based on individual joint mobility are in demand in both animation and medicine [1]. Medical models need to be highly accurate animated models less so, however if either are to be used in a real time environment they must have a low temporal cost (high performance). This work briefly explores Support Vector Machine neural networks as joint configuration classifiers that group joint configurations into invalid and valid. A far more detailed investigation is carried out into the use of topologically evolved feed forward neural networks for the generation of appropriately proportioned corrective components which when applied to an invalid joint configuration result in a valid configuration and the same configuration if the original configuration was valid. Discontinuous vector fields were used to represent constraints of varying size, dimensionality and complexity. This culminated in the creation corrective quaternion constraints represented by discontinuous vector fields, learned by topologically evolved neural networks and trained via the resilient back propagation algorithm. Quaternion constraints are difficult to implement and although alternative methods exist [2-6] the method presented here is superior in many respects. This method of joint constraint forms the basis of the contribution to knowledge along with the discovery of relationships between the continuity and distribution of samples in quaternion space and neural network performance. The results of the experiments for constraints on the rotation of limb with regular boundaries show that 3.7 x lO'Vo of patterns resulted in errors greater than 2% of the maximum possible error while for irregular boundaries 0.032% of patterns resulted in errors greater than 7.5%.

abstract: Many studies on human walking pattern assume that adult gait is characterized by bilateral symmetrical behavior. It is well understood that maintaining symmetry in walking patterns increases energetic eciency. We present a framework to provide a quantitative assessment of human walking patterns, especially assessments related to symmetric and asymmetric gait patterns purely based on glide reflection. A Gliding symmetry score is calculated from the data obtained from Motion Capture(MoCap) system. Six primary joints (Shoulder, Elbow, Palm, Hip, Knee, Foot) are considered for this study. Two dierent abnormalities were chosen and studied carefully. All the two gaits were mimicked in controlled environment. The framework proposed clearly showed that it could distinguish the abnormal gaits from the ordinary walking patterns. This framework can be widely used by the doctors and physical therapists for kinematics analysis, bio-mechanics, motion capture research, sports medicine and physical therapy, including human gait analysis and injury rehabilitation. / Dissertation/Thesis / Masters Thesis Electrical Engineering 2017

No description available.

Thesis. 1978. Ph.D.--Massachusetts Institute of Technology. Dept. of Mechanical Engineering. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING. / Bibliography: leaves 126-135. / Ph.D.

人體姿態估計系統是用於從視頻圖像中判斷人體在空間中姿態的系統。該系統面臨的主要的問題有：人體姿態空間的維度高；人體四肢的深度信息不確定；人體可以穿多種衣服；人體經常會被自身遮擋。多攝像頭系統可以觀察到人體同一姿態的更多數據，因此可以有效的克服人體姿態估計的不確定性。在本研究中，我們採用多種方法研究多攝像頭人體姿態估計系統，並提出了一種融合多種約束的框架。 / 在多攝像頭系統中，可以用到的約束包括：（一）圖像觀測約束：估計的人體姿態投影到圖像中需要和所有視角的觀察一致，（二）人體姿態可行性約束：人體部位之間要滿足身體連接約束並且估計所得的人體姿態要符合真實人體的要求，（三）三維剛體約束：從不同視角觀察到的人體要保持空間一致性，（四）行為約束：人體的姿態應與先驗的行為信息保持一致。本研究的目標是開發出一個可以同時利用上述約束的多攝像頭系統，該系統將可以同時無縫的整合多個攝像頭，並且可以穩定有效的估計人體的三維姿態。本文研究了基於單目系統的三維人體姿態估計方法，並基於約束一和約束二提出了一個新的人體模型估計人體姿態；本文提出仿射立體投影模型，並將該模型用於整合多個視角的觀察數據，從而使姿態估計同時得到約束一，約束二和約束三的支持；本文展示了如何使用多視角行為流形庫同時應用以上提到的四種約束，並有效的估計三維人體姿態；最後我們提出了基於流形庫的部分輸入高斯過程處理人體姿態估計腫的遮擋問題。 / 本論文有以下貢獻：（1）首次提出了仿射立體投影模型並將其用於描述三維剛體約束。使用這種方法，可以方便的將三維剛體約束集成於由底向上的人體姿態估計框架。（2）將人體姿態可行性約束以及三維剛體約束同時集成於多視角流型庫。即使在多行為的環境中，該方法也可以直接把多視角觀察數據映射至人體姿態空間。（3）通過綜合分析多個視角的數據，該系統可以有效的克服自我遮擋問題。（4）該系統易於擴展，基於仿射立體投影模型的方法和基於多視角流形庫的方法都可以用在多於三個攝像頭的系統中。 / A human pose estimation system is to determine the full human body pose in space from merely video data. Key difficulties of this problem include: full body kinematics is of high dimensionality, limb depths are ambiguous, people can impose various clothes, and there are often self-occlusions. The use of multiple views could enhance robustness of the solution toward uncertainties, as more data are collected about the same pose. In this research, we study multi-view based human pose estimation by exploring a variety of approaches and propose a framework that integrates multiple constraints. / In a multiple view system, the constraints that could be applied for human pose estimation include: (1) Image evidence: the projection of the estimated 3D human body should satisfy the 2D observations in all views, (2) Feasible human pose: neighboring body parts should be connected according to the body articulation and all joints angles should stay feasible, (3) 3D object rigidity: the corresponding parts over all views should satisfy the multi-view consistency, and (4) Action context: the detected results should be in line with prior knowledge about the possible “activities“. The objective of this research is to develop a multiple view system that could embed all the above constraints in a natural way while integrate more cameras into the system seamlessly to enhance robustness. Specifically, we investigate the part based monocular 3D estimation algorithm and develop a novel human model to assist the pose inference based on the constraint (1) and (2); we propose an affine stereo model to associate multiple views’ data so that body pose inference is supported by constraint (1), (2) and (3) simultaneously; we present how to apply multi-view activity manifold library to associate multiple views and estimate human pose in 3D efficiently so that all the four constraints are integrated into one framework; and we finally propose a partial-input Gaussian process to handle the body occlusion problem within the manifold library framework. / The thesis has four contributions: (1), an affine stereo approach is developed to efficiently explore the object rigidity, and this constraint is integrated into a bottom-up framework smoothly. (2), a multi-view visual manifold library is proposed to capture the human body articulation and rigidity in the multi-activity context, simplifying the pose estimation into a direct mapping from multi-view image evidence to 3D pose. (3), the multi-view system efficiently solves the self-occlusion problem by analyzing multi-view’s data. (4), the multi-view system is designed to be scalable; both the affine stereo based approach and the multi-view visual manifold library based approach could be applied to systems with more than 3 cameras. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Wang, Zibin. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 144-150). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese. / ABSTRACT --- p.i / 摘要 --- p.iii / ACKNOWLEDGEMENTS --- p.v / TABLE OF CONTENTS --- p.vi / LIST OF FIGURES --- p.xi / LIST OF TABLES --- p.xviii / Chapter Chapter One : --- Introduction --- p.1 / Chapter 1.1 --- Background --- p.1 / Chapter 1.2 --- Goals --- p.3 / Chapter 1.3 --- Challenges --- p.3 / Chapter 1.3.1 --- High Dimensional State Space --- p.3 / Chapter 1.3.2 --- Observations --- p.4 / Chapter 1.3.3 --- Multiple Views Integration --- p.6 / Chapter 1.4 --- Summary of the Approach --- p.7 / Chapter 1.5 --- Thesis Overview --- p.9 / Chapter Chapter Two : --- Background --- p.10 / Chapter 2.1 --- Top-down Framework --- p.11 / Chapter 2.1.1 --- Background Subtraction --- p.11 / Chapter 2.1.2 --- Deterministic Approach --- p.13 / Chapter 2.1.3 --- Sampling based Approach --- p.14 / Chapter 2.1.4 --- Regression based Method --- p.16 / Chapter 2.2 --- Bottom-up Framework --- p.17 / Chapter 2.2.1 --- Efficient Pictorial Structure --- p.18 / Chapter 2.2.2 --- Discriminative Part Detector --- p.19 / Chapter 2.2.3 --- Sampling based Inference --- p.20 / Chapter 2.2.4 --- Temporal Information --- p.21 / Chapter 2.3 --- Human Pose Estimation using Range Sensor --- p.21 / Chapter 2.4 --- Conclusion --- p.22 / Chapter Chapter Three : --- Pose Estimation from Single View --- p.23 / Chapter 3.1 --- Related Works --- p.25 / Chapter 3.2 --- The 3D Human Model --- p.26 / Chapter 3.3 --- Acquiring the Appearance Facet --- p.29 / Chapter 3.3.1 --- 2D Appearance Extraction from Each Training Image --- p.30 / Chapter 3.3.2 --- Acquiring 3D Appearance --- p.31 / Chapter 3.4 --- Data Driven Belief Propagation for Pose Estimation --- p.32 / Chapter 3.4.1 --- A Bayesian Formulation --- p.32 / Chapter 3.4.2 --- Belief Propagation --- p.34 / Chapter 3.4.3 --- Importance Function Sampling --- p.37 / Chapter 3.5 --- Experimental Results --- p.40 / Chapter 3.6 --- Conclusion --- p.45 / Chapter Chapter Four : --- Integrating Multiple Views using Affine Stereo Model --- p.46 / Chapter 4.1 --- Related Works --- p.48 / Chapter 4.2 --- Human Model and Problem Formulation --- p.50 / Chapter 4.3 --- Associating Multiple Image Streams --- p.53 / Chapter 4.3.1 --- Linear Relation of Multiple Views --- p.54 / Chapter 4.3.2 --- Rank Constraint --- p.58 / Chapter 4.4 --- Human Pose Estimation System using Multi-view and Other Constraints --- p.62 / Chapter 4.4.1 --- Body Part Candidates from Discriminative Body Part Detector --- p.63 / Chapter 4.4.2 --- From Body Part Candidates to Body Candidates in each view --- p.65 / Chapter 4.4.3 --- Associating Body Candidates across Views --- p.67 / Chapter 4.5 --- Experimental Results --- p.74 / Chapter 4.5.1 --- Evaluation of the Multi-view Linear Relationship --- p.74 / Chapter 4.5.2 --- Performance over the HumanEva Dataset --- p.79 / Chapter 4.6 --- Conclusion --- p.86 / Chapter Chapter Five : --- Integrating Multiple Views using Activity Manifold Library --- p.88 / Chapter 5.1 --- Related Works --- p.90 / Chapter 5.2 --- Multi-view Manifold Library --- p.93 / Chapter 5.2.1 --- Body Representation in Space and Views --- p.94 / Chapter 5.2.2 --- Human-orientation-dependent Multi-view Visual Manifold --- p.95 / Chapter 5.3 --- Human Pose Estimation in 3D via Multi-view Manifold --- p.97 / Chapter 5.3.1 --- Find Multi-view Body Hypothesis in 2D --- p.97 / Chapter 5.3.2 --- Mutual Selection between Multi-view Body Hypothesises and Manifolds --- p.99 / Chapter 5.4 --- Experimental Results --- p.102 / Chapter 5.4.1 --- Synthetic Data Test --- p.103 / Chapter 5.4.2 --- Real Image Evaluation --- p.108 / Chapter 5.4.3 --- Qualitative Test for Generalization Capability --- p.110 / Chapter 5.4.4 --- Calculation Speed --- p.114 / Chapter 5.5 --- Conclusion --- p.115 / Chapter Chapter Six : --- Partial-Input Gaussian Process for Inferring Occluded Human Pose --- p.116 / Chapter 6.1 --- Related Works --- p.118 / Chapter 6.2 --- Human-orientation-invariant Multi-view Visual Manifold --- p.119 / Chapter 6.3 --- Human Pose estimation in 3D via Multi-view Manifold --- p.121 / Chapter 6.3.1 --- 2D Pre-processing --- p.121 / Chapter 6.3.2 --- Mutual Selection between Multi-view Body Hypothesises and Manifolds --- p.121 / Chapter 6.3.3 --- Occlusion Detection and Partial-input Gaussian Process --- p.122 / Chapter 6.4 --- Experimental Results --- p.126 / Chapter 6.4.1 --- Multi-view Manifolds and Evaluations for Different Views --- p.126 / Chapter 6.4.2 --- Evaluation for Occlusion Data --- p.131 / Chapter 6.4.3 --- Evaluation for Gavrila’s Dataset --- p.132 / Chapter 6.4.4 --- Qualitative Test for Generalization Capability --- p.134 / Chapter 6.5 --- Conclusion --- p.139 / Chapter Chapter Seven : --- Conclusions and Future Works --- p.140 / Chapter 7.1 --- Conclusion --- p.140 / Chapter 7.2 --- Limitation --- p.142 / Chapter 7.3 --- Future Directions --- p.142 / Bibliography --- p.144

Assessment of different gait patterns of daily living could provides useful information in studying one individual's stability and mobility during locomotion. As the foundation for better assessment of different gait patterns, the ability to automatically identity different patterns and walking surroundings provide valuable information for further understanding the relations between gait pattern and energy consumption. We apply Discrete Wavelet Transform (DWT) for feature generation and Fuzzy-logic based approach for designing the multi-class classifier to identify gait patterns among fiat walking, descending stairs, and ascending stairs based on continuous kinematic signals. / Falls in the aging population has always been one of the most challenging problems in public health care. We propose an automatic falling detection algorithm based on the analysis of plantar force on both feet, because plantar forces are an important parameters directly associated with postures of human locomotion. The proposed two-stage algorithm efficiently overcome the shortcomings of the widely proposed accelerometer or gyroscope based algorithms and could provide efficient assistant for automatic detection of falls once they occur. / Finally, the research of studying gait abnormalities is introduced. We develop the methodology for modeling and classifying abnormal gaits including toe-in, toe-out, over-supination, and heel walking via machine learning algorithms, hidden Markov models (HMM) and support vector machine (SVM) based on a suite of gait parameters. The trained classifiers can classify abnormal gait patterns mentioned above and the proposed methodology will make it possible to provide realtime feedback to assist persons with gait abnormalities in the development of a normal walking pattern in their daily life. / Keeping abnormal motion for long time will ultimately lead to pain in the feet, ankles, legs and skeletal disease, and badly influences the skelecton growth especially for children and adolescents. In biomedicine, gait analysis has been proved as an useful approach. in revealing helpful insights into the recognition of motion abnormalities. Analysis of gait is commonly used as a routine procedure in identifying movement or posture related abnormalities of humans and aiding the therapeutic processes. Our goal is to monitor and study gaits of humans in order that proper motion adjustments can he advised to improve their posture style and long-term well being. / Most currently utilized measurement systems for motion and gait analysis have the shortcomings of that the monitoring and analysis of motion is constrained in a limited environment and human-related assistance is essential. All of them cannot be acceptable for the purpose of long-term monitoring and studying of motion abnormalities. In this thesis, a new concept of an inexpensive, compact, and lightweight shoe-integrated platform is introduced. The shoe-integrated system is composed of a suite of sensors for wirelessly capturing gait parameters and generating well qualified analysis results. The ideal platform requires no specialized equipment or lab setup, allowing data to be collected not only in the narrow confines of a research lab, but essentially anywhere, both indoors and outdoors. / To be one of the common postural abnormalities, postural kyphosis is studied and modeled. We apply Cascade Neural Networks with Node-Decoupled Extended Kalman Filtering (CNN-NDEKF) to train the model for this binary classification problem. This proposed study is of particular significance to provide feedback in the application of postural kyphosis rectification. / Chen, Meng. / "December 2009." / Adviser: Yangsheng Xu. / Source: Dissertation Abstracts International, Volume: 72-01, Section: B, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (leaves 120-130). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

Human balance control is a complex feedback system that must be adaptable and robust in an infinitely varying external environment. It is probable that there are many concurrent control loops occurring in the central nervous system that achieve stability for a variety of postural perturbations. Though many engineering models of human balance control have been tested, no models of how these controllers might operate within the nervous system have yet been developed. We have focused on building a model of a proprioceptive feedback loop with simulated neurons. The proprioceptive referenced portion of human balance control has been successfully modeled by a PD controller with a time delay and output torque positive feedback. For this model, angular position is measured at the ankle and corrective torque is applied about the joint to maintain a vertical orientation. In this paper, we construct a neural network that performs addition, subtraction, multiplication, differentiation and signal filtering to demonstrate that a simulated biological neural system based off of the engineering control model is capable of matching human test subject dynamics.

This thesis investigates walking patterns in healthy young people and in people with an increased risk of falling, and determines the physiological contributions to walking stability. First, a review of the relevant literature on techniques for assessing walking stability, age-related changes in balance and gait, and the contributions of vision, vestibular function, peripheral sensation and strength was undertaken. In response to a critical analysis of these findings, a new technique and protocol for the assessment of walking stability was developed. This involved measuring and analysing head and pelvis accelerations while subjects walked on a level surface and an irregular surface. Gait patterns were studied in 30 young healthy subjects and two groups known to be at increased risk of falling - 100 subjects over the age of 75, and 30 subjects with diabetic peripheral neuropathy. A series of vision, sensation, strength, reaction time and balance tests were also undertaken to identify subjects??? physiological abilities and risk of falls. Acceleration patterns of the head and pelvis differed according to physiological risk of falling, particularly when walking on the irregular surface. Those with a high risk of falling walked with a reduced velocity, cadence and step length, and exhibited less rhythmic acceleration patterns at the head and pelvis. Gait patterns were significantly associated with leg strength, peripheral sensation and reaction time. It is concluded that subjects with a high physiological risk of falling exhibit characteristic patterns of walking that indicate an impaired ability to control the movement of the pelvis and head, which may predispose to loss of balance.