Long range moiré patterns

Previous work has gone towards using moiré patterns formed with lenticular lenses to perform pose estimation for short ranges. This thesis investigates existing theory of moiré patterns, most notably the Fourier and first harmonic approximation models. This theory has been drawn upon to create a generalised model of planar moiré patterns in 3D. For example, those generated from two patterns with fine grids separated in space. This improves on previous research that does not investigate this specific kind of 3D pattern as closely. This thesis also developed a framework that simulates moiré patterns using this model. Along with this, the proposed framework can also solve pose information about a moiré pattern given an image. Experiments varying camera lateral translation were accurate for the close-range testing, with about 10 mm accuracy from a distance of 160 mm. Results from varying camera distance where 0–130 mm accuracy varied from ranges 100–2000 mm. A y-tilt estimation experiment was performed using the solver from this framework. At 3.116 m it was able to estimate an angle with an error of 5° for angles as wide as 30° and was able to estimate angles with an error of 0.25° for angles less than 5°. This is better than similar existing methods such as the Metria Moiré Phase Tracking marker’s maximum absolute errors of up to 2.8 mm and 2.1°

A structured light solution for detecting scapular dyskinesis

Scapular dyskinesis is a common occurrence in overhead athletes, i.e. athletes who participate in any sport where the upper arm and shoulder is used above the athlete’s head. However, no consensus has been reached on how to evaluate scapular dyskinesis quantitatively. In this thesis, we developed a measuring tool that can be used to evaluate certain key clinical parameters specific to scapular dyskinesis. The tool employs a 3D structured light computer vision approach to create a surface map of the soft-tissue across the scapula. This surface map is then analysed using surface curvature analysis techniques to identify the key clinical parameters associated with scapular dyskinesis. The main advantage of this method is that it provides a measurement tool that may facilitate future quantitative analysis of these key parameters. This may aid with diagnosis and monitoring of the condition by allowing measurement data to be collected both before and after treatment and rehabilitation. We expect that this tool will make the monitoring of treatment effectiveness easier while contributing to diagnostic computer vision

Bridging the Gap Between People, Mobile Devices, and the Physical World

Human-computer interaction (HCI) is being revolutionized by computational design and artificial intelligence. As the diversity of user interfaces shifts from personal desktops to mobile and wearable devices, yesterday’s tools and interfaces are insufficient to meet the demands of tomorrow’s devices. This dissertation describes my research on leveraging different physical channels (e.g., vibration, light, capacitance) to enable novel interaction opportunities. We first introduce FontCode, an information embedding technique for text documents. Given a text document with specific fonts, our method can embed user-specified information (e.g., URLs, meta data, etc) in the text by perturbing the glyphs of text characters while preserving the text content. The embedded information can later be retrieved using a smartphone in real time. Then, we present Vidgets, a family of mechanical widgets, specifically push buttons and rotary knobs that augment mobile devices with tangible user interfaces. When these widgets are attached to a mobile device and a user interacts with them, the nonlinear mechanical response of the widgets shifts the device slightly and quickly. Subsequently, this subtle motion can be detected by the Inertial Measurement Units (IMUs), which is commonly installed on mobile devices. Next, we propose BackTrack, a trackpad placed on the back of a smartphone to track finegrained finger motions. Our system has a small form factor, with all the circuits encapsulated in a thin layer attached to a phone case. It can be used with any off-the-shelf smartphone, requiring no power supply or modification of the operating systems. BackTrack simply extends the finger tracking area of the front screen, without interrupting the use of the front screen. Lastly, we demonstrate MoiréBoard, a new camera tracking method that leverages a seemingly irrelevant visual phenomenon, the moiré effect. Based on a systematic analysis of the moiré effect under camera projection, MoiréBoard requires no power nor camera calibration. It can easily be made at a low cost (e.g., through 3D printing) and ready to use with any stock mobile device with a camera. Its tracking algorithm is computationally efficient and can run at a high frame rate. It is not only simple to implement, but also tracks devices at a high accuracy, comparable to the state-of-the-art commercial VR tracking systems

State-of-The-Art and Applications of 3D Imaging Sensors in Industry, Cultural Heritage, Medicine, and Criminal Investigation

3D imaging sensors for the acquisition of three dimensional (3D) shapes have created, in recent years, a considerable degree of interest for a number of applications. The miniaturization and integration of the optical and electronic components used to build them have played a crucial role in the achievement of compactness, robustness and flexibility of the sensors. Today, several 3D sensors are available on the market, even in combination with other sensors in a “sensor fusion” approach. An importance equal to that of physical miniaturization has the portability of the measurements, via suitable interfaces, into software environments designed for their elaboration, e.g., CAD-CAM systems, virtual renders, and rapid prototyping tools. In this paper, following an overview of the state-of-art of 3D imaging sensors, a number of significant examples of their use are presented, with particular reference to industry, heritage, medicine, and criminal investigation applications

Precision of pose estimation using corner detection.

The aim of this research was to develop a method for recording ground truth with performance comparable to motion capture, in order to produce high-quality outdoor visual odometry datasets. A novel fiducial marker system was developed, featuring a smooth pattern which is used in an optimisation process to produce refined estimates. On average, precision was increased by 27 % compared to traditional fiducial markers. To investigate the limit of the increase in pose estimation precision possible with this method, the marker was modelled as a dense grid of checkerboard corners and the Cramér-Rao lower bound of the corresponding estimator was derived symbolically. This gave a lower bound for the variance of a pose estimated from a given image. The model was validated in simulation and using real images. The distribution of the error for a common checkerboard corner detector was evaluated to determine whether modelling it using independent and identically distributed Gaussian random variables was valid. In a series of experiments where images were collected from a tripod, a robot arm, and a slider-type electric actuator, it was determined that the error is usually normally distributed but its variance depends on the amount of lens blur in the image, and that any amount of motion blur can produce correlated results. Furthermore, in images with little blur (less than approximately one pixel) the estimates are biased, and both the bias and the variance are dependent on the location of the corner within a pixel. In real images, the standard deviation of the noise was around 80 % larger at the pixel edges than at the centre. The intensity noise from the image sensor was also found not to be identically distributed: in one camera, the standard deviation of the intensity noise varied by a factor of approximately four within the region around a checkerboard corner. This research suggests that it is possible to significantly increase fiducial marker pose estimation precision, presents a novel approach for predicting and evaluating pose estimation precision, and highlights sources of error not considered in prior work

An Experimental Technique for the Study of the Mechanical Behavior of Thin Film Materials at Micro- and Nano-Scale

An experimental technique has been presented to probe the mechanical behavior of thin film materials. The method is capable of tensile testing thin films on substrate and free-standing thin film specimens. A mechanical gripper was designed to address the current challenges in gripping thin film specimens. In order to measure the strain field across the gage section, the moire interferometry technique was used and the respective optical setup was designed. A versatile microfabrication process has been developed to fabricate free-standing dog-bone specimens. Aluminum was used as the model material; however, any other metallization material can be integrated in the process. Thin film specimens have been characterized using SEM, AFM, and TEM. A process has been developed to fabrication diffraction gratings on the specimen by FIB milling. Different grating geometries were fabricated and the diffraction efficiency of the gratings was characterized. The structural damage induced by the Ga+ ions during the FIB milling of the specimens was partially characterized using STEM and EDS. In order to extract the strain field information from the moire interferogram data, a numerical postprocessing technique was developed based on continuous wavelet transforms (CWT). The method was applied on simulated uniform and nonuniform strain fields and the wavelet parameters were tuned to achieve the best spatial localization and strain accuracy

Three-dimensional geometry characterization using structured light fields

Tese de doutoramento. Engenharia Mecânica. Faculdade de Engenharia. Universidade do Porto. 200

An Optimization Method for Estimating Joint Parameters of the Hip and Knee

Biomechanics, generally speaking, concerns the application of engineeringprinciples to the study of living things. This work is concerned withhuman movement analysis, a subfield of biomechanics, where the methodsof classical mechanics are applied to human movement. This field hascontributed to the general understanding of human movement, and itstechniques are used in the diagnosis and treatment of disease. Centralto the field is the process of measuring human movement. Since classicalmechanics deals with the motion of rigid bodies, and ideal measurementsystem would be able to accurately record the exact pose --- combinedposition and orientation --- of the bones. The techniques that reachthis ideal require exposure to radiation or the insertion of metalpins into bones. Non-invasive methods are far more commonly used,and these involve the optical tracking of special markers placed overthe skin on each segment of the body being studied. Motion capturesystems are able to accurately record the pose of the markers, butthey bear no repeatable relationship to the pose of the underlyingbone. Many techniques are employed to bridge the gap between the two.The most direct technique finds three or more points on each bonenear the surface of the skin, called Anatomical Landmarks (ALs), anduses them to define the bone\u27s pose relative to the motion trackingmarkers. There are concerns about the reliability of this method;the same experimenter performing this procedure multiple times onthe same subject will choose slightly different points on the bone,leading to variation in its orientation. The problem is exacerbatedwhen multiple experimenters are involved. This affects the abilityto compare data across time or between working groups; it may alsolead to erroneous interpretations of data. Furthermore, this techniquecannot be used directly to locate the hip joint center; instead, ALsat the pelvis are used as independent variables in a regression equationwhich statistically predicts the hip joint center location. Such techniqueshave begun to show reasonable reliability only recently. An alternative approach is to orient the bones based on a mathematicalanalysis of the motion of the tracking markers while the subject moves.This is the domain of functional and optimization methods. Functionalmethods are commonly used to find two joint parameters in particular:the center of the hip joint and the axis of rotation of the knee.Once found, these parameters are used to determine the orientationof the bones relative to the tracking markers. Functional methodsare subject specific and operator independent but may be biased dueto the presence of Soft Tissue Artifact (STA), which is the measurementerror caused by the movement of tissue in between the tracking markersand the underlying bone. Optimization methods estimate joint parametersby fitting a kinematic model of the joints under study to motion datawhich records a subject exercising those joints. Unlike functionalmethods, which estimate parameters for a single joint, optimizationmethods may estimate the parameters of multiple joints in some circumstances.The parameters of a kinematic model incorporating multiple jointsmay be estimated as long as the relative pose of the end segmentsof the model is measured with more Degrees of Freedom (DoF) than themodel itself possesses. The key insight of this work is thata kinematic model which contains a spherical hip joint and a 2 DoFcompound hinge knee joint may be fitted to motion data from the pelvisand lower leg. There are two benefits to this procedure. First, thethigh is known to be affected by a high degree of STA; by removingdependence on data from the thigh, this method gains the potentialfor more accurate joint parameter estimates. Second, once fitted tomovement data, the model provides an estimate of the pose of the femur.One may investigate STA at the thigh by comparing the pose of thethigh markers to the model\u27s estimate of the pose of the femur. Typically,medical imaging or invasive methods are required to investigate STA;this procedure is accessible and safe. In summary, this work presents a technique which has the potentialto make the non-invasive measurement of human movement more reliable.This technique also provides the possibility of estimating soft tissueartifact at the thigh in a safe and convenient manner