1,721,027 research outputs found
Modelling shape and parameterising style: an approach to the design of high-fashion shoe lasts
No full textA shoe's shape, captured by the shoe last, is designed based on the anatomical parameters of the foot. However, changing footwear fashions result in a variety of shapes and styles of last, which complicates the determination of ergonomic shoe forms. We propose a method for simple customisation of a shoe's style while retaining an ergonomic fit. 3D foot scans were used initialise the design of a shoe last based on the average foot shape of the target population. The shoe styles are then modelled as changes to the toe box, which is style dependent and thus, free to model, and the height of the heel lift, which is based on 3D geometric calculations linked to the anthropometric parameters of the foot. The proposed method was tested using consumer surveys. The results of the surveys showed an increase in comfort and satisfaction compared to shoe samples made with standard commercial lasts
Subject-specific identification of three dimensional foot shape deviations using statistical shape analysis
No full textAbstract: The high prevalence of foot pain, and its relation to foot shape, indicates the need for an expert system to identify foot shape abnormalities. Yet, to date, no such expert system exists that examines the full 3D foot shape and produces an intuitive explanation of why a foot is abnormal. In this work, we present the first such expert system that satisfies those goals. The system is based on the concept of model-based outlier detection: a statistical shape model (SSM) is generated from 186 3D optical foot scans of healthy feet. This model acts as a knowledge base which is then parameterized by one's demographic characteristics (e.g., age, weight, height, shoe size) through a multivariate regression. This regression introduces model flexibility as it allows the model to be fine tuned to a specific individual. This fine tuned model is then used as a baseline to which the individual's 3D foot scan can be compared using standard statistical tests (e.g. t-tests). These statistical tests are performed at each vertex along the foot surface to identify the degree and location of shape outliers. Our expert system was validated on foot scans from patients with hallux valgus and abnormal foot arches. As expected, our results varied per patient, confirming that feet with the same clinical classification still show high shape variability. Additionally, the foot shape abnormalities identified by our system not only agreed with the expected location and severity of the tested foot deformities, but our analysis of the full 3D foot shape was able to completely characterize the extent of those abnormalities for the first time. These results show that the combination of statistical shape modelling, multivariate regression, and statistical testing is powerful enough to perform outlier detection for 3D foot shapes. The resulting insights provided by this system could prove useful in both shoe design and clinical diagnosis. (C) 2020 Elsevier Ltd. All rights reserved
A GPU optimization workflow for real-time execution of ultra-high frame rate computer vision applications
Get PDFThis work proposes a GPU optimization methodology for real-time execution of ultra high frame rate applications with small frame sizes. While the use of GPUs for offline processing is well-established, real-time execution remains challenging due to the lack of real-time execution guarantees, especially for embedded GPUs. Our methodology introduces guidelines and a workfl ow by focusing on: (a) controlling latency by means of minimization of CPU-GPU interactions; (b) computation pruning; and (c) inter/intra-kernel optimizations. Furthermore, our approach takes advantage of multi-frame processing to attain signifi cantly higher throughput at the cost of increased latency when the application permits such trade-offs. To evaluate our optimization methodology, we applied it to the monitoring and controlling of laser powder bed fusion machines, a widely used metal additive manufacturing technique. Results show that in the considered application, the required performance could be obtained on a Jetson Xavier AGX platform, and by sacrificing latency, significantly higher throughput was achieved
Statistical Shape and Pose Model of the Forearm for Custom Splint Design
No full textAbstract: Custom splint design is becoming more common. However, poor 3D scan quality can negatively impact the design accuracy. This paper describes a method to build a 3D statistical shape and pose model of the forearm from 3dMD scans. The model is used to assist the registration of previously unseen forearms in a wide range of poses. We show that this model-based surface registration results in a good geometric fit, with accurate anatomical correspondences. This method could be used to upgrade low-resolution scans using a high-resolution model
Foot shape assessment techniques for orthotic and footwear applications : a methodological literature review
Get PDFIntroduction: Foot shape assessment is important to characterise the complex shape of a foot, which is in turn essential for accurate design of foot orthoses and footwear, as well as quantification of foot deformities (e.g., hallux valgus). Numerous approaches have been described over the past few decades to evaluate foot shape for orthotic and footwear purposes, as well as for investigating how one’s habits and personal characteristics influence the foot shape. This paper presents the developments reported in the literature for foot shape assessment.
Method: In particular, we focus on four main dimensions common to any foot assessment: (a) the choice of measurements to collect, (b) how objective these measurement procedures are, (c) how the foot measurements are analyzed, and (d) other common characteristics that can impact foot shape analysis.
Results: For each dimension, we summarize the most commonly used techniques and identify additional considerations that need to be made to achieve a reliable foot shape assessment.
Discussion: We present how different choices along these two dimensions impact the resulting foot assessment, and discuss possible improvements in the field of foot shape assessment
Towards material and process agnostic features for the classification of pore types in metal additive manufacturing
Get PDFThe manufacturing of metal parts via powder-bed fusion is often still facing quality issues due to microstructural porosity. Minimizing this porosity remains a priority and requires the optimization of printing process parameters. While the analysis of printed parts using X-ray computed tomography
can localize and identify the pore types (e.g. keyhole or lack-of-fusion pores), these pore types can be difficult to identify across printer settings and print materials. Therefore, there is a need for a material and process agnostic approach. This work presents such an approach by considering a set of geometric pore features that do not differ considerably across print scenarios. These features are then leveraged for supervised pore type classification. The distributions of pore features were analyzed in different materials and under varying laser parameters, showing that they behave in a generic way. For classification, it is observed that they outperform other features leveraged in the state-of-the-art for pore classification in a single material, reaching up to 93.0% accuracy. Additionally, accuracies up to 90.2% for cross-material classification were observed by training on pores of one material and validating on another. These results
pave the way to a general-purpose pore classification method usable across materials and process conditionssponsorship: imec ICON Vlaio|‘Vision in the Loop’ (HBC.2019.2808)status: Published onlin
Encoding Stability into Laser Powder Bed Fusion Monitoring Using Temporal Features and Pore Density Modelling
Get PDFIn laser powder bed fusion (LPBF), melt pool instability can lead to the development of pores in printed parts, reducing the part’s structural strength. While camera-based monitoring systems have been introduced to improve melt pool stability, these systems only measure melt pool stability in limited, indirect ways. We propose that melt pool stability can be improved by explicitly encoding stability into LPBF monitoring systems through the use of temporal features and pore density modelling. We introduce the temporal features, in the form of temporal variances of common LPBF monitoring features (e.g., melt pool area, intensity), to explicitly quantify printing stability. Furthermore, we introduce a neural network model trained to link these video features directly to pore densities estimated from the CT scans of previously printed parts. This model aims to reduce the number of online printer interventions to only those that are required to avoid porosity. These contributions are then implemented in a full LPBF monitoring system and tested on prints using 316L stainless steel. Results showed that our explicit stability quantification improved the correlation between our predicted pore densities and true pore densities by up to 42%
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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