This paper proposes a foot mapping-based representation of curves and surfaces which is a geometric generalization of signed distance functions. We present a first-order characterization of the footvector mapping in t...
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This paper proposes a foot mapping-based representation of curves and surfaces which is a geometric generalization of signed distance functions. We present a first-order characterization of the footvector mapping in terms of the differential geometric invariants of the represented shape and quantify the dependence of the spatial partial derivatives of the footvector mapping with respect to the principal curvatures at the footpoint. The practical applicability of foot mapping representations is highlighted by several fast iterative methods to compute the exact footvector mapping of the offset surface of constructive solid geometry (CSG) trees. The set operations for footpoint mappings are higher-order functions that map a tuple of functions to a single function, which poses a challenge for GPU implementations. We propose a code generation framework to overcome this that transforms CSG trees to the GLSL shader code.
Objectives: Tooth preparation is complicated because it requires the preparation of an abutment while simultaneously predicting the ideal shape of the tooth. This study aimed to develop and evaluate a system using aug...
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Objectives: Tooth preparation is complicated because it requires the preparation of an abutment while simultaneously predicting the ideal shape of the tooth. This study aimed to develop and evaluate a system using augmented reality (AR) head-mounted displays (HMDs) that provide dynamic navigation capabilities for tooth preparation. Methods: The proposed system utilizes optical see-through HMDs to overlay digital information onto the real world and enrich the user's environment. By integrating tracking algorithms and three-dimensional modeling, the system provides real-time visualization and navigation capabilities during tooth preparation by using two different visualization techniques. The experimental setup involved a comprehensive analysis of the distance to the surface and cross-sectional angles between the ideal and prepared teeth using three scenarios: traditional (without AR), overlay (AR-assisted visualization of the ideal prepared tooth), and cross-sectional (AR-assisted visualization with cross-sectional views and angular displays). Results: A user study (N = 24) revealed that the cross-sectional approach was more effective for angle adjustment and reduced the occurrence of over-reduction. Additional questionnaires revealed that the AR-assisted approaches were perceived as less difficult, with the cross-sectional approach excelling in terms of performance. Conclusions: Visualization and navigation using cross-sectional approaches have the potential to support safer tooth preparation with less overreduction than traditional and overlay approaches do. The angular displays provided by the cross-sectional approach are considered helpful for tooth preparation. Clinical significance: The AR navigation system can assist dentists during tooth preparation and has the potential to enhance the accuracy and safety of prosthodontic treatment.
We have developed a software tool called "GWGPM"that generates wallpaper group patterns for molecular visualization. Assuming a 2D image file has already been created using other chemical or biological softw...
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We have developed a software tool called "GWGPM"that generates wallpaper group patterns for molecular visualization. Assuming a 2D image file has already been created using other chemical or biological software, it can be fed into the software tool and generate all 17 wallpaper group patterns. The output can be exported as image files or files in other formats. While the software was developed for scientific purposes, it can also be used for entertainment since all operations in GWGPM are based on general 2D images.& COPY;2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://***/licenses/by/4.0/).
This article introduces Lester, a novel method to automatically synthesize retro-style 2D animations from videos. The method approaches the challenge mainly as an object segmentation and tracking problem. Video frames...
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This article introduces Lester, a novel method to automatically synthesize retro-style 2D animations from videos. The method approaches the challenge mainly as an object segmentation and tracking problem. Video frames are processed with the Segment Anything Model (SAM) and the resulting masks are tracked through subsequent frames with DeAOT, a method of hierarchical propagation for semi-supervised video object segmentation. The geometry of the masks' contours is simplified with the Douglas-Peucker algorithm. Finally, facial traits, pixelation and a basic rim light effect can be optionally added. The results show that the method exhibits an excellent temporal consistency and can correctly process videos with different poses and appearances, dynamic shots, partial shots and diverse backgrounds. The proposed method provides a more simple and deterministic approach than diffusion models based video-to-video translation pipelines, which suffer from temporal consistency problems and do not cope well with pixelated and schematic outputs. The method is also more feasible than techniques based on 3D human pose estimation, which require custom handcrafted 3D models and are very limited with respect to the type of scenes they can process.
Saliency-driven mesh simplification methods have shown promising results in main-taining visual detail, but effective simplification requires accurate 3D saliency maps. The conventional mesh saliency detection method ...
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Saliency-driven mesh simplification methods have shown promising results in main-taining visual detail, but effective simplification requires accurate 3D saliency maps. The conventional mesh saliency detection method may not capture salient regions in 3D models with texture. To address this issue, we propose a novel saliency detection method that fuses saliency maps from multi-view projections of textured models. Specifically, we introduce a texel descriptor that combines local convexity and chromatic aberration to capture texel saliency at multiple scales. Furthermore, we created a novel dataset that reflects human eye fixation patterns on textured models, which serves as an objective evaluation metric. Our experimental results demonstrate that our saliency-driven method outperforms existing approaches on several evaluation metrics. Our method source code can be accessed at https://***/bkballoon/mvsm-fusion and the dataset can be accessed at 10.5281/zenodo.8131602.
This systematic review provides an overview of augmented reality (AR) and its benefits in craniomaxillofacial surgery in an attempt to answer the question: Is AR beneficial for craniomaxillofacial surgery? This review...
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This systematic review provides an overview of augmented reality (AR) and its benefits in craniomaxillofacial surgery in an attempt to answer the question: Is AR beneficial for craniomaxillofacial surgery? This review includes a description of the studies conducted, the systems used and their technical characteristics. The search was performed in four databases: PubMed, Cochrane Library, Embase, and Web of Science. All journal articles published during the past 11 years related to AR, mixed reality, craniomaxillofacial, and surgery were considered in this study. From a total of 7067 articles identified using AR-and surgery-related keywords, 39 articles were finally selected. Based on these articles, a classification of study types, surgery types, devices used, metrics reported, and benefits were collected. The findings of this review indicate that AR could provide various benefits, addressing the challenges of conventional navigation systems, such as hand-eye coordination and depth perception. However, three main concerns were raised while performing this study: (1) it is complicated to aggregate the metrics reported in the articles, (2) it is difficult to obtain statistical value from the current studies, and (3) user evaluation studies are lacking. This article concludes with recommendations for future studies by addressing the latter points.
Background: computer vision studies and three-dimensional (3D) models are used to restore two-dimensional (2D) images. computer vision studies have been conducted in the computer graphic field, and due to its broad ap...
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Background: computer vision studies and three-dimensional (3D) models are used to restore two-dimensional (2D) images. computer vision studies have been conducted in the computer graphic field, and due to its broad applications, numerous related explorations have been performed. Methodology: To directly and effectively convey the design concept of the virtual vision technology, the graphic design was changed from 2D to 3D, which broadened the graphic design development space. Based on the 3D virtual vision and interactive design, this study constructed an interior design platform. After the detailed introduction of the function design of the 3D virtual visual effect displays of the interior design platform, the 3D virtual rendering functions of the interior design platform were designed. Results: When the traditional interior design platform was improved, panoramic information combined with 3D virtual vision technology can be used to record and analyze the results and to generate the corresponding image workflow for establishing a completely functional interior design platform. Based on this, ordinary and interior design platforms were comparatively analyzed. Conclusion: The interior design platform can accurately determine the interior landscape position and draw good 3D images.
In this special issue of IEEE Transactions on Visualization and computer graphics (TVCG), we are pleased to present the top papers from the 31th IEEE Conference on Virtual Reality and 3D User Interfaces (IEEE VR 2024)...
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In this special issue of IEEE Transactions on Visualization and computer graphics (TVCG), we are pleased to present the top papers from the 31th IEEE Conference on Virtual Reality and 3D User Interfaces (IEEE VR 2024), held March 16-21, 2024, in Orlando, Florida, US.
We introduce a semantically-enriched method of generating color schemes for various types of digital maps that reduces the energy consumption of the display device while preserving the quality of the original design. ...
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We introduce a semantically-enriched method of generating color schemes for various types of digital maps that reduces the energy consumption of the display device while preserving the quality of the original design. Energy-aware design intersects two important trends in cartography. First, as more maps are viewed today on mobile, battery life has become a central constraint influencing design. Second, there is increasing need for green computing, which encourages the efficient use of energy to limit environmental impacts. This paper focuses on one important aspect of energy-aware cartography: color design. Existing research on energy-aware color adjustment methods apply broadly to images or websites. However, the colors used in maps have more structured semantic relationships than most documents viewed on mobile devices, and efforts to account for these relationships while reducing energy consumption are limited. To fill this gap, we mathematically formalize energy-aware map-color adjustment as a constrained optimization problem: we define energy consumption as the objective function and model the preservation of semantic relationships as the search constraints. We evaluate our proposed method against a common color dimming method using four maps with different semantic relationships. The evaluation suggests that our proposed method better preserves the original color semantics.
Convolutional neural networks have achieved great success in computer vision, but incorrect predictions would be output when applying intended perturbations on original input. These human-indistinguishable replicas ar...
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Convolutional neural networks have achieved great success in computer vision, but incorrect predictions would be output when applying intended perturbations on original input. These human-indistinguishable replicas are called adversarial examples, which on this feature can be used to evaluate network robustness and security. White-box attack success rate is considerable, when already knowing network structure and parameters. But in a black-box attack, the adversarial examples success rate is relatively low and the transferability remains to be improved. This article refers to model augmentation which is derived from data augmentation in training generalizable neural networks, and proposes resizing invariance method. The proposed method introduces improved resizing transformation to achieve model augmentation. In addition, ensemble models are used to generate more transferable adversarial examples. Extensive experiments verify the better performance of this method in comparison to other baseline methods including the original model augmentation method, and the black-box attack success rate is improved on both the normal models and defense models.
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