This thesis will look at the importance of 3D Visualization within the planning process and addresses the issue of improving public participation within urban regeneration. The main aim of this research is therefore to discover what type of model the public require in terms of understanding future developments, which may in turn help them engage in the planning process. In order to achieve the main aim several other aims need to be established, such as; identifying the capacity of the profession in Wales to deliver 3D models of urban environments, evaluating software solutions to create 3D models of urban environments, and to explore emerging techniques that might contribute to the efficiency and economy of producing models of urban environments. These aims were realised through conducting surveys which targeted the Building Design Profession (BDP) and established which software packages were being used and for what purpose. A second survey was also conducted by means of an exhibition, which aimed to establish what the public require in regards to being presented with proposed developments. Other aims were realized through conducting trials. These examined the usability of different 3D CAD packages and the possibility of integrating CAD data with GIS, and how it could be used to quicken the modeling process. Results from these trials showed that through the use of workarounds there are possibilities of integrating CAD and GIS data. The research reported here indicates that members of the public have trouble understanding 2D Plans and Elevations and the data consistently demonstrates that more than 40% of participants chose 3D technology as a more understandable method of being shown future developments. The results from the two surveys show that although the majority (42.4%) of participants selected 3D technology as their preferred option, only 28% of participating Building Design Professionals in Wales use 3D computer packages, albeit not for presenting propose urban regeneration projects to the public. From the outset of this research the purpose has been to evaluate whether public participation will be increased if 3D technologies are provided to showcase proposed developments. The more efficient the modelling process, the more feasible and likely it will be that 3D CAD will one day be a paramount tool within the Planning Process. Numerous techniques were included to examine this efficiency.

This work describes the investigation of a new 3D capture method for acquisition and subsequent forensic analysis of bite mark injuries on human skin. When documenting bite marks with standard 2D cameras, errors in photographic technique can occur if best practice is not followed. Subsequent forensic analysis of the mark is problematic when a 3D structure is recorded in a 2D space. A 3D image capture and processing system might avoid the problems resulting from the 2D reduction process, simplifying the guidelines and reducing errors. The proposed solutions in this work are: conducting a review of the current 2D and three 3D capture methods, also a series of benchmarks for system assessment. Followed by a series of performance evaluations of the existing current 2D and two 3D methods. Further proposed solutions include, the design of a system specification for the practical reproducible acquisition of bite mark injuries. Finally a review of the validation process for forensic evidence presented to the courts. The results of the work are as follows: A 3D system is required to produce the correct 3D data of a bite mark and suspect dentition for forensic analysis. Such a system should be practical and consistent, if it is to replace the current de facto 2D systems. The MAVIS hardware can be considered a practical and consistent solution for producing the required 3D image of a bite mark for analysis; however, the MAVIS hardware cannot produce a satisfactory 3D image of a dental cast. At present a laser scanner is required to produce satisfactory results of a dental cast. Angular distortion and errors created by the user in 2D image capture can hinder the digital measurement process. 3D capture therefore introduces less operator error in the form of angular distortion.

No description available.

Avec l’augmentation des applications de sécurité, un sujet particulier a attiré plus d’attention que de nombreux autres domaines en reconnaissance de formes : la biométrie – la reconnaissance des personnes en fonction de leur physique et/ou de leurs traits comportementaux. Parmi ces traits, le visage se distingue par un compromis favorable entre accessibilité et fiabilité. Dans cette thèse, nous avons principalement travaillé sur une modalité relativement plus récente en reconnaissance du visage : la forme 3D. Plus avantageuse que son homologue en 2D, car intrinsèquement invariant aux changements d’illumination de pose, l’analyse 3D du visage se heurte encore à des défis majeurs tels que les déformations de surface du visage dues aux expressions ou occultations. En conséquence, une étude approfondie est effectuée sur ce sujet incluant le prétraitement des données 3D du visage, l’annotation automatique, la simulation d’altération et d’expressions en 3D, l’extraction de caractéristiques 3D et l’analyse locale de surface. / As the need and investment for security applications grow vastly, one particular topic has certainly been attracting higher attention than many other pattern recognition fields: biometrics – recognition of humans based on their physical and/or behavioral traits. Among those traits, face stands out with its favorable reconcilement between accessibility and reliability. In this doctoral dissertation, we principally investigate 3D shape which is a relatively more recent modality in face recognition. Being advantageous to its 2D counterpart for being intrinsically invariant to illumination and pose changes, 3D face recognition still encounters major challenges such as acquisition inadequacy or facial surface deformations due to expressions or occlusion. Bearing those in mind, a thorough study is carried out on this topic, including pre-processing of 3D facial data, automatic landmarking, facial expression and alteration simulations in 3D, 3D feature extraction and 3D regional surface analysis.

Specifically equipped and programmed robots are highly successful in controlled industrial environments such as automated production lines. For the transition of robots from such controlled uniform environments to unconstrained household environments with a large range of conditions and variations, a new paradigm is needed to prepare the robots for deployment. Robots need to be able to quickly adapt to their changing environments and learn on their own how to solve their tasks in novel situations. This dissertation focusses on the aspect of learning to predict the success of two-object means-end actions in a developmental way. E.g. the action of bringing one object into reach by pulling another, where the one object is on top of the other. Here it is the “on top” relation that affects the success of the action. Learning the preconditions for complex means-end actions via supervised learning can take several thousand training samples, which is impractical to generate, hence more rapid learning capabilities are necessary. Three contributions of this dissertation are used to solve the learning problem. 1. Inspired by infant psychology this dissertation investigates an approach to intrinsic motivation that is based on active learning, guiding the robot's exploration to create experience useful for improving classification performance. 2. This dissertation introduces histogram based 3D vision features that encode the relative spatial relations between surface points of object pairs, allowing a robot to reliably recognise the important spatial categories that affect means-end action outcomes. 3. Intrinsically encoded experience is extracted into symbolic category knowledge, encoding higher level abstract categories. These symbolic categories are used for knowledge transfer by using them to extend the state space of action precondition learning classifiers. Depending on the actions and their preconditions, the contributions of this dissertation enable a robot to achieve success prediction accuracies above 85% with ten training samples instead of approximately 1000 training samples that would otherwise be required. These results can be achieved when (a) the action preconditions can be easily identified from the used vision features or (b) the action preconditions to be learnt rest upon already existing knowledge, then it is possible to achieve these results by reusing the existing knowledge. This dissertation demonstrates, in simulation, an alternative to handcoding the knowledge required for a robot to interact with and manipulate objects in the environment. It shows that rapid learning, grounded in autonomous exploration, can be feasible if the necessary vision features are constructed and if existing knowledge is consistently reused.

published_or_final_version / Mechanical Engineering / Doctoral / Doctor of Philosophy

published_or_final_version / abstract / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

published_or_final_version / Computer Science / Doctoral / Doctor of Philosophy

published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

published_or_final_version / abstract / Mathematics / Doctoral / Doctor of Philosophy