A System for 3D Shape Estimation and Texture Extraction via Structured Light

Shape estimation is a crucial problem in the fields of computer vision, robotics and engineering. This thesis explores a shape from structured light (SFSL) approach using a pyramidal laser projector, and the application of texture extraction. The specific SFSL system is chosen for its hardware simplicity, and efficient software. The shape estimation system is capable of estimating the 3D shape of both static and dynamic objects by relying on a fixed pattern. In order to eliminate the need for precision hardware alignment and to remove human error, novel calibration schemes were developed. In addition, selecting appropriate system geometry reduces the typical correspondence problem to that of a labeling problem. Simulations and experiments verify the effectiveness of the built system. Finally, we perform texture extraction by interpolating and resampling sparse range estimates, and subsequently flattening the 3D triangulated graph into a 2D triangulated graph via graph and manifold methods

Semiautomated Skeletonization of the Pulmonary Arterial Tree in Micro-CT Images

We present a simple and robust approach that utilizes planar images at different angular rotations combined with unfiltered back-projection to locate the central axes of the pulmonary arterial tree. Three-dimensional points are selected interactively by the user. The computer calculates a sub- volume unfiltered back-projection orthogonal to the vector connecting the two points and centered on the first point. Because more x-rays are absorbed at the thickest portion of the vessel, in the unfiltered back-projection, the darkest pixel is assumed to be the center of the vessel. The computer replaces this point with the newly computer-calculated point. A second back-projection is calculated around the original point orthogonal to a vector connecting the newly-calculated first point and user-determined second point. The darkest pixel within the reconstruction is determined. The computer then replaces the second point with the XYZ coordinates of the darkest pixel within this second reconstruction. Following a vector based on a moving average of previously determined 3- dimensional points along the vessel\u27s axis, the computer continues this skeletonization process until stopped by the user. The computer estimates the vessel diameter along the set of previously determined points using a method similar to the full width-half max algorithm. On all subsequent vessels, the process works the same way except that at each point, distances between the current point and all previously determined points along different vessels are determined. If the difference is less than the previously estimated diameter, the vessels are assumed to branch. This user/computer interaction continues until the vascular tree has been skeletonized

The Tracking Performance of Distributed Recoverable Flight Control Systems Subject to High Intensity Radiated Fields

It is known that high intensity radiated fields (HIRF) can produce upsets in digital electronics, and thereby degrade the performance of digital flight control systems. Such upsets, either from natural or man-made sources, can change data values on digital buses and memory and affect CPU instruction execution. HIRF environments are also known to trigger common-mode faults, affecting nearly-simultaneously multiple fault containment regions, and hence reducing the benefits of n-modular redundancy and other fault-tolerant computing techniques. Thus, it is important to develop models which describe the integration of the embedded digital system, where the control law is implemented, as well as the dynamics of the closed-loop system. In this dissertation, theoretical tools are presented to analyze the relationship between the design choices for a class of distributed recoverable computing platforms and the tracking performance degradation of a digital flight control system implemented on such a platform while operating in a HIRF environment. Specifically, a tractable hybrid performance model is developed for a digital flight control system implemented on a computing platform inspired largely by the NASA family of fault-tolerant, reconfigurable computer architectures known as SPIDER (scalable processor-independent design for enhanced reliability). The focus will be on the SPIDER implementation, which uses the computer communication system known as ROBUS-2 (reliable optical bus). A physical HIRF experiment was conducted at the NASA Langley Research Center in order to validate the theoretical tracking performance degradation predictions for a distributed Boeing 747 flight control system subject to a HIRF environment. An extrapolation of these results for scenarios that could not be physically tested is also presented

Creation of Large Scale Face Dataset Using Single Training Image

Face recognition (FR) has become one of the most successful applications of image analysis and understanding in computer vision. The learning-based model in FR is considered as one of the most favorable problem-solving methods to this issue, which leads to the requirement of large training data sets in order to achieve higher recognition accuracy. However, the availability of only a limited number of face images for training a FR system is always a common problem in practical applications. A new framework to create a face database from a single input image for training purposes is proposed in this dissertation research. The proposed method employs the integration of 3D Morphable Model (3DMM) and Differential Evolution (DE) algorithms. Benefitting from DE\u27s successful performance, 3D face models can be created based on a single 2D image with respect to various illumination and pose contexts. An image deformation technique is also introduced to enhance the quality of synthesized images. The experimental results demonstrate that the proposed method is able to automatically create a virtual 3D face dataset from a single 2D image with high performance. Moreover the new dataset is capable of providing large number of face images equipped with abundant variations. The validation process shows that there is only an insignificant difference between the input image and the 2D face image projected by the 3D model. Research work is progressing to consider a nonlinear manifold learning methodology to embed the synthetically created dataset of an individual so that a test image of the person will be attracted to the respective manifold for accurate recognition

Action Recognition in Videos: from Motion Capture Labs to the Web

This paper presents a survey of human action recognition approaches based on visual data recorded from a single video camera. We propose an organizing framework which puts in evidence the evolution of the area, with techniques moving from heavily constrained motion capture scenarios towards more challenging, realistic, "in the wild" videos. The proposed organization is based on the representation used as input for the recognition task, emphasizing the hypothesis assumed and thus, the constraints imposed on the type of video that each technique is able to address. Expliciting the hypothesis and constraints makes the framework particularly useful to select a method, given an application. Another advantage of the proposed organization is that it allows categorizing newest approaches seamlessly with traditional ones, while providing an insightful perspective of the evolution of the action recognition task up to now. That perspective is the basis for the discussion in the end of the paper, where we also present the main open issues in the area.Comment: Preprint submitted to CVIU, survey paper, 46 pages, 2 figures, 4 table

Models and methods for biometric motion identification Bartosz

Human motion is a complex signal with many different properties depending on various factors: age, gender, physical condition, emotions etc. Nevertheless there is a hypothesis which claims that human motion can be a source for biometric analysis and person identification. In the paper some methods to analyze and compare different motions are presented. Methods are examined for usefulness in motion identification. We distinguish time-series and frequency analysis for rotational signals describing mainly the motion of legs. The results of experiments are presented taking into consideration different motion representations