Using facial feature extraction to enhance the creation of 3D human models

The creation of personalised 3D characters has evolved to provide a high degree of realism in both appearance and animation. Further to the creation of generic characters the capabilities exist to create a personalised character from images of an individual. This provides the possibility of immersing an individual into a virtual world. Feature detection, particularly on the face, can be used to greatly enhance the realism of the model. To address this innovative contour based templates are used to extract an individual from four orthogonal views providing localisation of the face. Then adaptive facial feature extraction from multiple views is used to enhance the realism of the model

Image processing for plastic surgery planning

This thesis presents some image processing tools for plastic surgery planning. In particular, it presents a novel method that combines local and global context in a probabilistic relaxation framework to identify cephalometric landmarks used in Maxillofacial plastic surgery. It also uses a method that utilises global and local symmetry to identify abnormalities in CT frontal images of the human body. The proposed methodologies are evaluated with the help of several clinical data supplied by collaborating plastic surgeons

Flexible shape extraction for micro/nano scale structured surfaces.

Surface feature is the one of the most important factors affecting the functionality and reliability of micro scale patterned surfaces. For micro scale patterned surface characterisation, it’s important to extract the surface feature effectively and accurately. The active contours, known as “snakes”, have been successfully used to segment, match and track the objects of interest. The active contours have been applied to facial boundary detection, medical image processing, motion correction, etc. In this paper, surface feature extraction techniques based on active contours have been investigated. Parametric active contour models and geometric active contour models have been presented. Also, a group of examples has been selected here to demonstrate the feasibility and applicability of the surface pattern extraction techniques based on active contours. At last, experimental results will be given and discussed

Improved facial feature fitting for model based coding and animation

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Active modelling of virtual humans

This thesis provides a complete framework that enables the creation of photorealistic 3D human models in real-world environments. The approach allows a non-expert user to use any digital capture device to obtain four images of an individual and create a personalised 3D model, for multimedia applications. To achieve this, it is necessary that the system is automatic and that the reconstruction process is flexible to account for information that is not available or incorrectly captured. In this approach the individual is automatically extracted from the environment using constrained active B-spline templates that are scaled and automatically initialised using only image information. These templates incorporate the energy minimising framework for Active Contour Models, providing a suitable and flexible method to deal with the adjustments in pose an individual can adopt. The final states of the templates describe the individual’s shape. The contours in each view are combined to form a 3D B-spline surface that characterises an individual’s maximal silhouette equivalent. The surface provides a mould that contains sufficient information to allow for the active deformation of an underlying generic human model. This modelling approach is performed using a novel technique that evolves active-meshes to 3D for deforming the underlying human model, while adaptively constraining it to preserve its existing structure. The active-mesh approach incorporates internal constraints that maintain the structural relationship of the vertices of the human model, while external forces deform the model congruous to the 3D surface mould. The strength of the internal constraints can be reduced to allow the model to adopt the exact shape of the bounding volume or strengthened to preserve the internal structure, particularly in areas of high detail. This novel implementation provides a uniform framework that can be simply and automatically applied to the entire human model

Dental Biometrics: Human Identification Using Dental Radiograph

Biometric is the science and innovation of measuring and analyzing biological information.In information technology, biometric refers to advancements that measures and analyzes human body attributes,for example,DNA, eye retinas, fingerprints and irises,face pattern,voice patterns,and hand geometry estimations,for identification purposes.The primary motivation behind scientific dentistry is to distinguish expired people,for whom different method for recognizable proof(e.g.,unique finger impression,face,and so on.)are not accessible.Dental elements survives most of the PM events which may disrupt or change other body tissues,e.g. casualties of motor vehicles mishaps,fierce violations,and work place accident,whose bodies could be deformed to such a degree,that identification even by a family member is neither desirable nor reliable.Dental Biometric utilises dental radiographs to distinguish casualties.The radiographs procured after the casualty's demise are called post-mortem radiograph and the radiograph obtained when the casualty was alive is called ante-mortem radiograph.The objective of dental biometric is to match the unidentified individual's post-mortem radiograph against a database of labelled antemortem radiograph.This thesis proposes a novel method for the contour extraction from dental radiographs.The proposed algorithm of Active Contour Model or the Snake model is used for this purpose. A correctly detected contour is essential for proper feature extraction.This thesis only works on the contour detection.The method has been tested on some radiographs images and is found to produce desired output.However,the input radiograph image may be of low quality,may suffer a clear separation between two adjacent teeth.In that case the method will not be able to produce a satisfactory result.There is a need of pre-processing(e.g. contrast enhancement) before the active contour detection model can be applie

Lip Localization Algorithm Using Gabor Filters

This paper describes a lip localization algorithm within a still image frame for subsequent tracking and audiovisual speech recognition processing. A Gabor filter-based feature space is promoted as a means to localize lips within an image based off of shape. This filtered space is shown to effectively differentiate facial features, including lips, from their backgrounds and to bound the full extent of the lips within a face-classified region of interest. Extensive training and test sets are used to justify design decisions and performance