A PCA approach to the object constancy for faces using view-based models of the face

The analysis of object and face recognition by humans attracts a great deal of interest, mainly because of its many applications in various fields, including psychology, security, computer technology, medicine and computer graphics. The aim of this work is to investigate whether a PCA-based mapping approach can offer a new perspective on models of object constancy for faces in human vision. An existing system for facial motion capture and animation developed for performance-driven animation of avatars is adapted, improved and repurposed to study face representation in the context of viewpoint and lighting invariance. The main goal of the thesis is to develop and evaluate a new approach to viewpoint invariance that is view-based and allows mapping of facial variation between different views to construct a multi-view representation of the face. The thesis describes a computer implementation of a model that uses PCA to generate example- based models of the face. The work explores the joint encoding of expression and viewpoint using PCA and the mapping between viewspecific PCA spaces. The simultaneous, synchronised video recording of 6 views of the face was used to construct multi-view representations, which helped to investigate how well multiple views could be recovered from a single view via the content addressable memory property of PCA. A similar approach was taken to lighting invariance. Finally, the possibility of constructing a multi-view representation from asynchronous view-based data was explored. The results of this thesis have implications for a continuing research problem in computer vision – the problem of recognising faces and objects from different perspectives and in different lighting. It also provides a new approach to understanding viewpoint invariance and lighting invariance in human observers

Camera positioning for 3D panoramic image rendering

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University London.Virtual camera realisation and the proposition of trapezoidal camera architecture are the two broad contributions of this thesis. Firstly, multiple camera and their arrangement constitute a critical component which affect the integrity of visual content acquisition for multi-view video. Currently, linear, convergence, and divergence arrays are the prominent camera topologies adopted. However, the large number of cameras required and their synchronisation are two of prominent challenges usually encountered. The use of virtual cameras can significantly reduce the number of physical cameras used with respect to any of the known camera structures, hence adequately reducing some of the other implementation issues. This thesis explores to use image-based rendering with and without geometry in the implementations leading to the realisation of virtual cameras. The virtual camera implementation was carried out from the perspective of depth map (geometry) and use of multiple image samples (no geometry). Prior to the virtual camera realisation, the generation of depth map was investigated using region match measures widely known for solving image point correspondence problem. The constructed depth maps have been compare with the ones generated using the dynamic programming approach. In both the geometry and no geometry approaches, the virtual cameras lead to the rendering of views from a textured depth map, construction of 3D panoramic image of a scene by stitching multiple image samples and performing superposition on them, and computation of virtual scene from a stereo pair of panoramic images. The quality of these rendered images were assessed through the use of either objective or subjective analysis in Imatest software. Further more, metric reconstruction of a scene was performed by re-projection of the pixel points from multiple image samples with a single centre of projection. This was done using sparse bundle adjustment algorithm. The statistical summary obtained after the application of this algorithm provides a gauge for the efficiency of the optimisation step. The optimised data was then visualised in Meshlab software environment, hence providing the reconstructed scene. Secondly, with any of the well-established camera arrangements, all cameras are usually constrained to the same horizontal plane. Therefore, occlusion becomes an extremely challenging problem, and a robust camera set-up is required in order to resolve strongly the hidden part of any scene objects. To adequately meet the visibility condition for scene objects and given that occlusion of the same scene objects can occur, a multi-plane camera structure is highly desirable. Therefore, this thesis also explore trapezoidal camera structure for image acquisition. The approach here is to assess the feasibility and potential of several physical cameras of the same model being sparsely arranged on the edge of an efficient trapezoid graph. This is implemented both Matlab and Maya. The quality of the depth maps rendered in Matlab are better in Quality

Imaging methods for understanding and improving visual training in the geosciences

Experience in the field is a critical educational component of every student studying geology. However, it is typically difficult to ensure that every student gets the necessary experience because of monetary and scheduling limitations. Thus, we proposed to create a virtual field trip based off of an existing 10-day field trip to California taken as part of an undergraduate geology course at the University of Rochester. To assess the effectiveness of this approach, we also proposed to analyze the learning and observation processes of both students and experts during the real and virtual field trips. At sites intended for inclusion in the virtual field trip, we captured gigapixel resolution panoramas by taking hundreds of images using custom built robotic imaging systems. We gathered data to analyze the learning process by fitting each geology student and expert with a portable eye- tracking system that records a video of their eye movements and a video of the scene they are observing. An important component of analyzing the eye-tracking data requires mapping the gaze of each observer into a common reference frame. We have made progress towards developing a software tool that helps automate this procedure by using image feature tracking and registration methods to map the scene video frames from each eye-tracker onto a reference panorama for each site. For the purpose of creating a virtual field trip, we have a large scale semi-immersive display system that consists of four tiled projectors, which have been colorimetrically and photometrically calibrated, and a curved widescreen display surface. We use this system to present the previously captured panoramas, which simulates the experience of visiting the sites in person. In terms of broader geology education and outreach, we have created an interactive website that uses Google Earth as the interface for visually exploring the panoramas captured for each site

Coordination of appearance and motion data for virtual view generation of traditional dances

A novel method is proposed for virtual view generation of traditional dances. In the proposed framework, a traditional dance is captured separately for appearance registration and motion registration. By coordinating the appearance and motion data, we can easily control virtual camera motion within a dancer-centered coordinate system. For this purpose, a coordination problem should be solved between the appearance and motion data, since they are captured separately and the dancer moves freely in the room. The present paper shows a practical algorithm to solve it. A set of algorithms are also provided for appearance and motion registration, and virtual view generation from archived data. In the appearance registration, a 3D human shape is recovered in each time from a set of input images after suppressing their backgrounds. By combining the recovered 3D shape and a set of images for each time, we can compose archived dance data. In the motion registration, stereoscopic tracking is accomplished for color markers placed on the dancer. A virtual view generation is formalized as a color blending among multiple views, and a novel and efficient algorithm is proposed for the composition of a natural virtual view from a set of images. In the proposed method, weightings of the linear combination are calculated from both an assumed viewpoint and a surface normal.</p

Spherical Image Processing for Immersive Visualisation and View Generation

This research presents the study of processing panoramic spherical images for immersive visualisation of real environments and generation of in-between views based on two views acquired. For visualisation based on one spherical image, the surrounding environment is modelled by a unit sphere mapped with the spherical image and the user is then allowed to navigate within the modelled scene. For visualisation based on two spherical images, a view generation algorithm is developed for modelling an indoor manmade environment and new views can be generated at an arbitrary position with respect to the existing two. This allows the scene to be modelled using multiple spherical images and the user to move smoothly from one sphere mapped image to another one by going through in-between sphere mapped images generated

Structural Optimization of a Distributed Actuation System in a Flexible In-Plane Morphing Wing

Structural weight and efficiency are hurdles for morphing aircraft being realizable on the full-scale level. The optimal distribution and orientation of actuators throughout an in-plane flexible morphing wing structure is investigated. The drive to minimize structural weight causes a wing to be more flexible and the location and orientation of the actuators become more critical as the structure becomes more flexible. NextGen\u27s N-MAS morphing wing is used as a case study. The wing is modeled as a number of unit cells assembled in a scissor-like structure, each comprised of four linkages pinned together and an actuator. The flexible skin of the wing is modeled with a nonlinear material stretched between two opposing vertices. It will be shown that the optimal orientation of the actuators will vary depending on the loading conditions and initial configuration of the wing. Sequential quadratic programming (SQP) optimization techniques are utilized to orient those actuators and effectively size the members of the structure. The goal is to minimize weight while maximizing the geometric advantage and efficiency. The constraints are member stresses and the force transferred to the actuators is not to be greater than the force the actuator is able to produce. Matlab® code is developed to do the SQP optimization while NASTRAN™ is utilized to do the nonlinear finite element analysis required to evaluate the objective function and constraints. The single-cell results are compared to experimental data to validate the finite element model (FEM) and optimization routine. A three-cell experiment is designed by utilizing aeroelastic scaling techniques. Matlab is used to develop the scaling problem while the actual scaling is done as an optimization in NASTRAN. The objective for scaling the wing is to minimize the differences in the non-dimensional displacements and strain energies between the two models, using the element cross-sectional dimensions as design variables