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During the undertaken research and development, two major systems were designed. These were; a prototype force sensor, and a movement measurement system. Both the developed systems were designed for the intended field of insect research, but were developed using very different underlying principles. The force measurement system uses the piezo-electric effect induced in piezo-electric bimorph elements to produce a measure of force exerted on the sensor. The movement measurement system on the other hand uses computer vision (CV) techniques to find and track the three dimensional (3D) position of markers on the insect, and thereby record the pose of the insect. To further increase the usefulness of the two measurement systems, a prototype graphical user interface (GUI) was produced to encapsulate the functionality of the systems and provide an end user with a more complete and functional research tool. The GUI allows a user to easily define the parameters required for the CV operations and presents the results of these operations to the user in an easily understood visual format. The GUI is also intended to display force measurements in a graphical means to make them easily interpreted. The GUI has been named Weta Evaluation Tracking and Analysis (WETA). Testing on the developed prototype force sensor shows that the piezo-electric bimorph elements provide an adequate measure of force exerted on them, when the voltage signal produced by an element is integrated. Furthermore, the testing showed that the developed force sensor layout produces an adequate measure of forces in the two horizontal linear degrees of freedom (DOF), but the prototype did not produce a good measure of forces in the vertical linear DOF. Development and testing of the movement measurement system showed that stereo vision techniques have the ability to produce accurate measurements of 3D position using two cameras. Although, when testing these techniques with one of the cameras replaced by a mirror, the system produced less than satisfactory results. Further testing on the feature detection and tracking portions of the movement system showed that even though these systems were implemented in a relatively simple way, they were still adequate in their associated operations. However, it was found that with some simple changes in colour spaces used during feature detection, the performance of the feature detection system in varying illumination was greatly improved. The tracking system on the other hand, operated adequately using just its associated basic principles. During the development of both prototype measurement systems, a number of conclusions were formulated that indicated areas of future development. These areas include; advanced force sensor configurations, force sensor miniaturisation, design of a force plate, improvement of feature detection and tracking, and refining of the stereo vision equipment.

This dissertation addresses the problem of employing 3D depth information on solving a number of traditional challenging computer vision/graphics problems. Humans have the abilities of perceiving the depth information in 3D world, which enable humans to reconstruct layouts, recognize objects and understand the geometric space and semantic meanings of the visual world. Therefore it is significant to explore how the 3D depth information can be utilized by computer vision systems to mimic such abilities of humans. This dissertation aims at employing 3D depth information to solve vision/graphics problems in the following aspects: scene understanding, image enhancements and 3D reconstruction and modeling. In addressing scene understanding problem, we present a framework for semantic segmentation and object recognition on urban video sequence only using dense depth maps recovered from the video. Five view-independent 3D features that vary with object class are extracted from dense depth maps and used for segmenting and recognizing different object classes in street scene images. We demonstrate a scene parsing algorithm that uses only dense 3D depth information to outperform using sparse 3D or 2D appearance features. In addressing image enhancement problem, we present a framework to overcome the imperfections of personal photographs of tourist sites using the rich information provided by large-scale internet photo collections (IPCs). By augmenting personal 2D images with 3D information reconstructed from IPCs, we address a number of traditionally challenging image enhancement techniques and achieve high-quality results using simple and robust algorithms. In addressing 3D reconstruction and modeling problem, we focus on parametric modeling of flower petals, the most distinctive part of a plant. The complex structure, severe occlusions and wide variations make the reconstruction of their 3D models a challenging task. We overcome these challenges by combining data driven modeling techniques with domain knowledge from botany. Taking a 3D point cloud of an input flower scanned from a single view, each segmented petal is fitted with a scale-invariant morphable petal shape model, which is constructed from individually scanned 3D exemplar petals. Novel constraints based on botany studies are incorporated into the fitting process for realistically reconstructing occluded regions and maintaining correct 3D spatial relations. The main contribution of the dissertation is in the intelligent usage of 3D depth information on solving traditional challenging vision/graphics problems. By developing some advanced algorithms either automatically or with minimum user interaction, the goal of this dissertation is to demonstrate that computed 3D depth behind the multiple images contains rich information of the visual world and therefore can be intelligently utilized to recognize/ understand semantic meanings of scenes, efficiently enhance and augment single 2D images, and reconstruct high-quality 3D models.

Chronic lateral instability of the ankle (CLI), defined as frequent sprains and recurrent giving way, difficulty in walking and running on uneven surface, is often connected with pain and swollen ankles. It occurs in 10 to 20 percent after acute ankle injuries. Mechanical instability of the talocrural and subtalar joint, peroneal weakness and impaired proprioception has been suggested as etiological factors. Aim. To investigate the natural course in conservatively treated patients with CLI. To assess the mechanical stability in patients with CLI by measuring the three dimensional motions in the talus, the fibula and the calcaneus in relation to the tibia during different testing procedures pre- and postoperatively. To determine if CLI is associated with proprioceptive deficiency. Patients and Methods. This Thesis includes 127 ankles in 78 patients (30 women, 48 men) with CLI. Thirty-seven patients were followed up 20 years after their first contact with the orthopaedic department because of CLI. Forty-six ankles were evaluated radiographically and the result was compared with a gender- and age - matched control-material. The neuromuscular response to a sudden angular displacement of the ankles was studied in 15 ankles in 13 patients using EMG. Thirty-six patients entered a prospective study using roentgen stereophotogrammetric analysis (RSA) in which the ankles were tested at manual adduction, adduction with predetermined torque, with and without external support and at drawer tests (40 N and 160N). Twenty-seven patients were followed five years postoperatively. Result. After 20 years 22 patients, conservatively treated still suffered from instability of the ankle and ten had recurrent giving way symptoms even on plane surface. Six ankles in the patient group and four in the control group displayed osteoarthritic changes Prolonged ipsilateral reaction time (m. per. long, and m. tib. ant.) was found in patients with CLI indicating proprioceptive insufficiency. Increased talar adduction and a tendency toward increased total translation of the talar center was found in ankles with CLI. Concomitant fibular rotations and translations were found but with no conclusive deviation in the ankles with symptoms. The talo-calcaneal adduction reached the same level in the patient and control groups regardless of symptoms. External support (ankle brace) increased the talar stability. The use of predetermined torque and constrained testing procedure did not add information compared with the manual test Twenty-five patients graded the result as excellent or good five years after lateral ligament reconstruction. Talar stability (decreased adduction and translation) was increased two years postoperatively and was improved or remained the same at five years without comprising the range of motion. Conclusion. In more than half the cases symptoms of CLI did not resolve spontaneously. Minor degenerative changes was found after twenty years, but not to a greater extent than in a control group. CLI was associated with proprioceptive insufficiency and talocrural but not subtalar instability. Increased ankle stability can be obtained by the use of an ankle brace and by an anatomical ligament reconstruction. / <p>Diss. (sammanfattning) Umeå : Umeå universitet, 1994</p> / digitalisering@umu

Closing the control loop of a manipulator robot with vision feedback is widelyknown. It concerns nowadays all areas of robotics. Such a return can make a comparison between a desired state and current state, using visual measurements. The main objective of this doctoral thesis is to design several types of kinematic control laws for stereo visual servoing. It strongly involves the formalism of the task function which is a well-known and useful mathematical tool to express the visual error as a function of state vectors.We have investigated the decoupling between the rotational and translational velocities control laws together with the epipolar constraint with a stereo visual feedback.That is why, the visual measurements and features used in this thesis are the 3Dstraight lines.The interests of this type of visual features rely on the robustness against the noise, and the possibility to represent straight lines or other features like points or planes pairs by the Plücker coordinates, as a 3D straight line can be represented as well by two points or the intersection of two planes. This makes all the control laws designed in this thesis valid for another visual features like points

Dans cette thèse nous avons l'intention d'enquêter sur la complémentarité des données auditives et visuelles sensorielles pour la construction d'une interprétation de haut niveau d'une scène. L'audiovisuel (AV) d'entrée reçus par le robot est une fonction à la fois l'environnement extérieur et de la localisation réelle du robot qui est étroitement liée à ses actions. La recherche actuelle dans AV analyse de scène a eu tendance à se concentrer sur les observateurs fixes. Toutefois, la preuve psychophysique donne à penser que les humains utilisent petite tête et les mouvements du corps, afin d'optimiser l'emplacement de leurs oreilles à l'égard de la source. De même, en marchant ou en tournant, le robot mai être en mesure d'améliorer les données entrantes visuelle. Par exemple, dans la perception binoculaire, il est souhaitable de réduire la distance de vue à un objet d'intérêt. Cela permet à la structure 3D de l'objet à analyser à une profondeur de résolution supérieure.

In recent years there has been significant progress in increasing the scope, accuracy and flexibility of 3D photography methods. However there are still significant open problems where complex optical properties of mirroring or transparent objects cause many assumptions of traditional algorithms to break down. In this work we present three approaches that attempt to deal with some of these challenges using a few camera views and simple illumination. First, we consider the problem of reconstructing the 3D position and surface normal of points on a time-varying refractive surface. We show that two viewpoints are sufficient to solve this problem in the general case, even if the refractive index is unknown. We introduce a novel ``stereo matching'' criterion called refractive disparity, appropriate for refractive scenes, and develop an optimization-based algorithm for individually reconstructing the position and normal of each point projecting to a pixel in the input views. Second, we present a new method for reconstructing the exterior surface of a complex transparent scene with inhomogeneous interior. We capture images from each viewpoint while moving a proximal light source to a 2D or 3D set of positions giving a 2D (or 3D) dataset per pixel, called the scatter-trace. The key is that while light transport within a transparent scene's interior can be exceedingly complex, a pixel's scatter trace has a highly-constrained geometry that reveals the direct surface reflection, and leads to a simple ``Scatter-trace stereo'' algorithm for computing the exterior surface geometry. Finally, we develop a reconstruction system for scenes with reflectance properties ranging from diffuse to specular. We capture images of the scene as it is illuminated by a planar, spatially non-uniform light source. Then we show that if the source is translated to a parallel position away from the scene, a particular scene point integrates a magnified region of light from the plane. We observe this magnification at each pixel and show how it relates to the source-relative depth of the surface. Next we show how calibration relating the camera and source planes allows for robustness to specular objects and recovery of 3D surface points.

A stereo vision system is a robust method to sense the distance information in a scene. This research explores the stereo vision system from the fundamentals of stereo vision and the computer stereo vision algorithm to the final implementation of the system on a FPGA chip. In a stereo vision system, images are captured by a pair of stereo image sensors. The distance information can be derived from the disparities between the stereo image pair, based on the theory of binocular geometry. With the increasing focus on 3D vision, stereo vision is becoming a hot topic in the areas of computer games, robot vision and medical applications. Particularly, most stereo vision systems are expected to be used in real-time applications. In this thesis, several stereo correspondence algorithms that determine the disparities between stereo image pair are examined. The algorithms can be categorized into global stereo algorithms and local stereo algorithms depending on the optimization techniques. The global algorithms examined are the Dynamic Time Warp (DTW) algorithm and the DTW with quantization algorithm, while the local algorithms examined are the window based Sum of Squared Differences (SSD), Sum of Absolute Differences (SAD) and Census transform correlation algorithms. With analysis among them, the window based SAD correlation algorithm is proposed for implementation on a FPGA platform. The proposed algorithm is implemented onto an Altera DE2 board featuring an Altera Cyclone II 2C35 FPGA. The implemented module of the algorithm is simulated using ModelSim-Altera to verify the correctness of its functionality. Along with a pair of stere image sensors and a LCD monitor, a stereo vision system is built. The entire system realizes a real-time video frame rate of 16.83 frames per second with an image resolution of 640 by 480 and produces disparity maps in which the objects are clearly distinguished by their relative distance information.

The estimation of optical flow has become a vital research field in image sequence analysis especially in past two decades, which found applications in many fields such as stereo optics, video compression, robotics and computer vision. In this thesis, the complex wavelet based algorithm for the estimation of optical flow developed by Magarey and Kingsbury is implemented and investigated. The algorithm is based on a complex version of the discrete wavelet transform (CDWT), which analyzes an image through blocks of filtering with a set of Gabor-like kernels with different scales and orientations. The output is a hierarchy of scaled and subsampled orientation-tuned subimages. The motion estimation algorithm is based on the relationship between translations in image domain and phase shifts in CDWT domain, which is satisfied by the shiftability and interpolability property of CDWT. Optical flow is estimated by using this relationship at each scale, in a coarse-to-fine (hierarchical) manner, where information from finer scales is used to refine the estimates from coarser scales. The performance of the motion estimation algorithm is investigated with various image sequences as input and the effects of the options in the algorithm like curvature-correction, interpolation kernel between levels and some parameter values like confidence threshold iv maximum number of CDWT levels and minimum finest level of detail are also experimented and discussed. The test results show that the method is superior to other well-known algorithms in estimation accuracy, especially under high illuminance variations and additive noise.

In very few mobile robotic applications stereo vision based navigation and mapping is used because dealing with stereo images is very hard and very time consuming. Despite all the problems, stereo vision still becomes one of the most important resources of knowing the world for a mobile robot because imaging provides much more information than most other sensors. Real robotic applications are very complicated because besides the problems of finding how the robot should behave to complete the task at hand, the problems faced while controlling the robot&rsquo / s internal parameters bring high computational load. Thus, finding the strategy to be followed in a simulated world and then applying this on real robot for real applications is preferable. In this study, we describe an algorithm for object recognition and cognitive map formation using stereo image data in a 3D virtual world where 3D objects and a robot with active stereo imaging system are simulated. Stereo imaging system is simulated so that the actual human visual system properties are parameterized. Only the stereo images obtained from this world are supplied to the virtual robot. By applying our disparity algorithm, depth map for the current stereo view is extracted. Using the depth information for the current view, a cognitive map of the environment is updated gradually while the virtual agent is exploring the environment. The agent explores its environment in an intelligent way using the current view and environmental map information obtained up to date. Also, during exploration if a new object is observed, the robot turns around it, obtains stereo images from different directions and extracts the model of the object in 3D. Using the available set of possible objects, it recognizes the object.