Paul Siebert

A discrete Reeb graph approach for the segmentation of human body scans

Segmentation of 3D human body (HB) scan is a very challenging problem in applications exploiting human scan data. To tackle this problem, we propose a topological approach based on discrete Reeb graph (DRG) which is an extension of the classical Reeb graph to unorganized cloud of 3D points. The essence of the approach is detecting critical nodes in the DRG thus permitting the extraction of branches that represent the body parts. Because the human body shape representation is built upon global topological features that are preserved so long as the whole structure of the human body does not change, our approach is quite robust against noise, holes, irregular sampling, moderate reference change and posture variation. Experimental results performed on real scan data demonstrate the validity of our method.

Topological segmentation of discrete human body shapes in various postures based on geodesic distance

This paper extends our previous Reeb graph approach based on a new Morse function, namely geodesic distance, to segment whole body scan data into primary body parts in various postures. Because of the bending invariance of geodesic distance, the resulting Reeb graph can remain stable in a large range of postures. Consequently, the approach is capable of segmenting data within the posture range. The application of geodesic distance also brings the independence of coordinate frame selection. We present a number of experiments conducted on both real body 3D scan samples and simulated datasets to demonstrate the validity of the approach.

Psychological status as a function of residual scarring and facial asymmetry after surgical repair of cleft lip and palate.

Objective Objective measure of scarring and three-dimensional (3D) facial asymmetry after surgical correction of unilateral cleft lip (UCL) and unilateral cleft lip (UCLP). It was hypothesized that the degree of scarring or asymmetry would be correlated with poorer psychological function. Design In a cross-sectional design, children underwent 3D imaging of the face and completed standardized assessments of self-esteem, depression, and state and trait anxiety. Parents rated childrens adjustment with a standard scale. Setting Glasgow Dental School, School of Medicine, College of Medical, Veterinary and Life Sciences. Patients Fifty-one children aged 10 years with UCLP and 43 with UCL were recruited from the cohort treated with the surgical protocol of the CLEFTSIS managed clinical network in Scotland. Methods Objective assessment to determine the luminance and redness of the scar and facial asymmetry. Depression, anxiety, and a self-esteem assessment battery were used for the psychological analysis. Results Cleft cases showed superior psychological adjustment when compared with normative data. Prevalence of depression matched the population norm. The visibility of the scar (luminance ratio) was significantly correlated with lower self-esteem and higher trait anxiety in UCLP children (P = .004). Similar but nonsignificant trends were seen in the UCL group. Parental ratings of poorer adjustment also correlated with greater luminance of the scar. Conclusions The objectively defined degree of postoperative cleft scarring was associated with subclinical symptoms of anxiety, depression, and low self-esteem.

A Precise Method for Cloth Configuration Parsing Applied to Single-arm Flattening

In this paper, we investigate the contribution that visual perception affords to a robotic manipulation task in which a crumpled garment is flattened by eliminating visually detected wrinkles. In order to explore and validate visually guided clothing manipulation in a repeatable and controlled environment, we have developed a hand-eye interactive virtual robot manipulation system that incorporates a clothing simulator to close the effector-garment-visual sensing interaction loop. We present the technical details and compare the performance of two different methods for detecting, representing and interpreting wrinkles within clothing surfaces captured in high-resolution depth maps. The first method we present relies upon a clustering-based method for localizing and parametrizing wrinkles, while the second method adopts a more advanced geometry-based approach in which shape-topology analysis underpins the identification of the cloth configuration (i.e., maps wrinkles). Having interpreted the state of the cloth configuration by means of either of these methods, a heuristic-based flattening strategy is then executed to infer the appropriate forces, their directions and gripper contact locations that must be applied to the cloth in order to flatten the perceived wrinkles. A greedy approach, which attempts to flatten the largest detected wrinkle for each perception-iteration cycle, has been successfully adopted in this work. We present the results of our heuristic-based flattening methodology which relies upon clustering-based and geometry-based features respectively. Our experiments indicate that geometry-based features have the potential to provide a greater degree of clothing configuration understanding and, as a consequence, improve flattening performance. The results of experiments using a real robot (as opposed to simulated robot) also confirm our proposition that a more effective visual perception system can advance the performance of cloth manipulation.

The definitions of three-dimensional landmarks on the human face: an interdisciplinary view

The analysis of shape is a key part of anatomical research and in the large majority of cases landmarks provide a standard starting point. However, while the technology of image capture has developed rapidly and in particular three‐dimensional imaging is widely available, the definitions of anatomical landmarks remain rooted in their two‐dimensional origins. In the important case of the human face, standard definitions often require careful orientation of the subject. This paper considers the definitions of facial landmarks from an interdisciplinary perspective, including biological and clinical motivations, issues associated with imaging and subsequent analysis, and the mathematical definition of surface shape using differential geometry. This last perspective provides a route to definitions of landmarks based on surface curvature, often making use of ridge and valley curves, which is genuinely three‐dimensional and is independent of orientation. Specific definitions based on curvature are proposed. These are evaluated, along with traditional definitions, in a study that uses a hierarchical (random effects) model to estimate the error variation that is present at several different levels within the image capture process. The estimates of variation at these different levels are of interest in their own right but, in addition, evidence is provided that variation is reduced at the observer level when the new landmark definitions are used.

Data Extraction from Dense 3-D Surface Models

Stereo-photogrammetry involves the use of pairs of cameras to extend standard photographic methods by recovering depth information through triangulation (Ayoub et al. 1998). The resulting data consist of a point-cloud of three-dimensional observations, providing a digital representation of the surface of the object of interest. The number of observations can typically be many thousands, providing a rich source of information on object shape. This can be represented efficiently as an irregular triangular mesh, in Virtual Reality Modelling Language form.

FASTR: Using Local Structure Tensors as a Similarity Metric☆

Abstract We describe a novel structural image descriptor for image registration called the Fractionally Anisotropic Structural Tensor Representation (FASTR), calculated from the local structural tensor (LST). The metric has several characteristics that are advantageous for multi-modality registration, such as not depending on absolute voxel intensities, and being insensitive to slowly varying in- tensity inhomogeneities across the image. This latter property is very useful, since many imaging modalities suffer from such artefacts. Registration accuracy is tested on both computed tomography (CT) to cone-beam CT (CBCT) rigid registration, and CT to magnetic resonance (MR) rigid registration. The performance is compared with Mutual Information (MI) metric and the Self Similarity Context (SSC) descriptor. The results show that, for images with significant intensity inhomogeneity, FASTR produced more accurate results than MI, and faster results than SSC. The results suggest FASTR gives similar benefits in images with intensity inhomogeneity, but at a fraction of the computation and memory demand.

LABELLING OF THREE DIMENSIONAL HUMAN BODY SCANS: A TOPOLOGICAL APPROACH

Whole human body scanners are 3D imaging devices which are capable of capturing a computerized format of whole body shape, thus permitting automatic extraction of the different body measurements. This requires the segmentation of scan data into subsets corresponding to the functional human body parts. Such a task is quite challenging due to the articulated and the deformable aspects of the human body shape. The attempts made so far suffer from various limitations, such as being restricted to standard specific posture and vulnerability to scan data corruption. This paper proposes a general framework that aims towards overcoming these challenges. One of the salient features of this framework is that it can cope with moderate posture variations around the standard posture, in addition of being quite robust against noise, holes and irregular sampling. Experimental results performed on real and synthetic data confirmed the validity, effectiveness and robustness of our framework.