by jsendak | Feb 20, 2024 | Computer Science
The article discusses a technique to address the challenges associated with surface-surface intersection in computer-aided design (CAD). Surfaces, particularly non-uniform rational B-spline surfaces (NURBS), are commonly used in geometric design. However, when surfaces intersect, trimmed surfaces can emerge, leading to complexities in CAD applications.
One of the main issues with trimmed surfaces is that their parametric domain is not usually a standard shape like a square or rectangle. Instead, it is often bounded by curves. This makes it difficult for downstream applications like computer-aided engineering (CAE) to process the data effectively. Additionally, NURBS surfaces struggle to maintain a closed form when dealing with trimmed surfaces. As a result, a specialized data structure for intersection curves is typically required to support downstream applications. However, this data structure is not standardized in the CAD system, resulting in inefficient calculations.
To address these challenges, the paper proposes a reparameterization or normalization technique for Bezier surfaces, which are a specific case of NURBS. By transforming the trimmed surface into a collection of Bezier surface patches in a standard parametric domain [0,1]X[0,1], the authors aim to eliminate the trimmed surface. The boundary curve of each normalized Bezier surface patch can then be replaced by the intersection curve, resulting in a watertight representation along the boundary. This approach effectively bridges the gap between CAD and CAE, ensuring seamless integration and eliminating any gaps or overlaps that may occur during preprocessing.
Overall, this technique offers a promising solution to the challenges associated with surface-surface intersection in CAD. By normalizing trimmed surfaces into Bezier surface patches, it simplifies the data structure and improves efficiency in downstream applications. Further research and experimentation could focus on evaluating the performance of this technique with different types of surfaces and exploring its applicability to various CAD systems and workflows. Ultimately, this technique has the potential to enhance the overall accuracy and reliability of CAD models, making them more suitable for downstream analysis and applications.
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by jsendak | Feb 17, 2024 | Computer Science
arXiv:2402.09720v1 Announce Type: new
Abstract: Low latency and high synchronization among users are critical for emerging multi-user virtual interaction applications. However, the existing ground-based cloud solutions are naturally limited by the complex ground topology and fiber speeds, making it difficult to pace with the requirement of multi-user virtual interaction. The growth of low earth orbit (LEO) satellite constellations becomes a promising alternative to ground solutions. To fully exploit the potential of the LEO satellite, in this paper, we study the satellite server selection problem for global-scale multi-user interaction applications over LEO constellations. We propose an effective server selection framework, called SpaceMeta, that jointly selects the ingress satellite servers and relay servers on the communication path to minimize latency and latency discrepancy among users. Extensive experiments using real-world Starlink topology demonstrate that SpaceMeta reduces the latency by 6.72% and the interquartile range (IQR) of user latency by 39.50% compared with state-of-the-art methods.
Expert Commentary: The Future of Multi-User Virtual Interaction with LEO Satellites
The article highlights the significance of low latency and high synchronization in multi-user virtual interaction applications, which are crucial for providing a seamless and immersive experience to users. However, the existing ground-based cloud solutions face limitations due to complex ground topology and fiber speeds, making it challenging to meet the requirements of these applications. This paves the way for exploring alternative solutions, such as leveraging low earth orbit (LEO) satellite constellations.
LEO satellite constellations offer a promising alternative to ground solutions by providing global coverage and reducing latency issues caused by the constraints of ground-based infrastructure. The article introduces SpaceMeta, an effective server selection framework specifically designed for global-scale multi-user interaction applications over LEO constellations. This framework aims to optimize server selection to minimize latency and latency discrepancies among users.
SpaceMeta takes into account both ingress satellite servers and relay servers on the communication path, ensuring efficient data transmission and reducing latency for enhanced user experience. By jointly selecting these servers, SpaceMeta effectively addresses the challenges posed by multi-user interaction applications in a global context.
The research conducted in this study includes extensive experiments using real-world Starlink topology, demonstrating the effectiveness of SpaceMeta compared to existing state-of-the-art methods. The results indicate a reduction in latency by 6.72% and a significant decrease in the interquartile range (IQR) of user latency by 39.50%, showcasing its potential to enhance the performance of multi-user virtual interaction applications over LEO constellations.
Relevance to Multimedia Information Systems and Virtual Realities
The concepts discussed in this article align with the broader field of multimedia information systems, where real-time communication, low latency, and high synchronization play a crucial role. Multi-user virtual interaction applications heavily rely on multimedia content, including audio, video, and animations, to create immersive virtual environments. The seamless delivery and synchronization of this multimedia content is essential for a seamless user experience.
LEO satellite constellations provide an intriguing solution for overcoming the limitations of traditional ground-based communication infrastructure. By integrating these satellites into the server selection process, SpaceMeta introduces a multi-disciplinary approach combining concepts from satellite communication, network optimization, and multimedia information systems.
The technology behind virtual realities (VR), augmented reality (AR), and artificial reality (AR) can greatly benefit from the advancements discussed in this article. These immersive technologies heavily rely on real-time interactions among users, and any delay or latency can disrupt the user experience. By reducing latency and discrepancies through effective server selection, SpaceMeta can enhance the performance and reliability of these immersive technologies.
Conclusion
The research presented in this article highlights the potential of LEO satellite constellations in addressing the challenges of multi-user virtual interaction applications. Through the development of the SpaceMeta framework, the authors provide a solution that optimizes server selection to minimize latency and improve synchronization among users. This has significant implications for the field of multimedia information systems, as well as virtual realities, augmented reality, and artificial reality technologies.
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by jsendak | Feb 17, 2024 | Computer Science
Expert Commentary: VR-CAD Framework for Immersive CAD Data Modification
In this poster, the authors present a novel framework that combines virtual reality (VR) and computer-aided design (CAD), enabling users to modify parametric CAD data in an immersive environment. This integration of VR and CAD has the potential to revolutionize the way designers and engineers interact with 3D models, making the design process more intuitive and efficient.
One of the key advantages of this VR-CAD framework is the ability for users to modify parameter values of CAD data using co-localized 3D shape-based interaction. Traditionally, CAD modeling requires users to manually input parameter values to adjust the shape of an object. With the inclusion of VR technology, users can now manipulate 3D shapes in a much more intuitive and natural way.
The system architecture described in the poster is crucial for the successful implementation of this framework. By leveraging the power of virtual reality headsets and motion-tracking devices, users can fully immerse themselves in the CAD environment and interact with the models using their hands or other input devices. This level of immersion allows for a more intuitive and engaging design process.
The interaction technique described in the poster further enhances the user experience by utilizing co-localized 3D shape-based interaction. This means that users can directly manipulate the 3D shapes in VR space, effectively bridging the gap between physical and digital design representation. This approach not only simplifies the design process but also allows for real-time visualization of design changes, enabling designers to make quick and informed decisions.
Looking ahead, this VR-CAD framework has the potential for various applications in industries such as architecture, automotive design, product development, and simulation. By enabling designers to immerse themselves in a virtual environment, they can better visualize and evaluate their designs before moving on to prototyping or production. Additionally, this framework opens up possibilities for collaborative design sessions, where multiple designers can work together in the same virtual environment, making real-time design modifications and exchanging ideas.
In conclusion, the presented VR-CAD framework holds significant promise for improving the CAD design process. By incorporating virtual reality and co-localized 3D shape-based interaction, designers and engineers can now modify parametric CAD data in a more intuitive and immersive manner. This technology has the potential to enhance productivity, creativity, and collaboration in the field of CAD design.
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by jsendak | Feb 16, 2024 | Computer Science
arXiv:2402.09062v1 Announce Type: new
Abstract: Digital watermarking enables protection against copyright infringement of images. Although existing methods embed watermarks imperceptibly and demonstrate robustness against attacks, they typically lack resilience against geometric transformations. Therefore, this paper proposes a new watermarking method that is robust against geometric attacks. The proposed method is based on the existing HiDDeN architecture that uses deep learning for watermark encoding and decoding. We add new noise layers to this architecture, namely for a differentiable JPEG estimation, rotation, rescaling, translation, shearing and mirroring. We demonstrate that our method outperforms the state of the art when it comes to geometric robustness. In conclusion, the proposed method can be used to protect images when viewed on consumers’ devices.
Expert Commentary: Robust Geometric Watermarking for Image Protection
This article discusses a new watermarking method that aims to address the challenge of geometric transformations in protecting images against copyright infringement. While existing methods are effective in embedding watermarks imperceptibly and withstanding various attacks, they often fall short when it comes to resilience against geometric transformations.
The proposed method builds upon the HiDDeN architecture, which utilizes deep learning techniques for watermark encoding and decoding. By introducing new noise layers, such as differentiable JPEG estimation, rotation, rescaling, translation, shearing, and mirroring, the authors demonstrate improved robustness against geometric attacks.
The multi-disciplinary nature of this research is noteworthy. It combines concepts from several fields, including image processing, deep learning, and computer vision, to address a specific challenge in the broader field of multimedia information systems.
Watermarking techniques are widely utilized in multimedia systems to protect intellectual property and prevent unauthorized use. Enhancing the protection against geometric transformations is crucial, as it not only contributes to the overall robustness of the watermark but also ensures the integrity of the copyrighted content.
Moreover, this research aligns with advancements in virtual realities, augmented reality, and artificial reality. As these technologies continue to evolve, the need for secure and resilient watermarking methods becomes increasingly important. By protecting images when viewed on consumer devices, the proposed method contributes to ensuring the authenticity and ownership of digital content in virtual and augmented reality environments.
In conclusion, this paper presents a promising approach to robust geometric watermarking for image protection. Through the utilization of deep learning techniques and the incorporation of various geometric transformations, the proposed method demonstrates superior performance compared to existing state-of-the-art methods. This research holds significant potential in safeguarding the integrity of copyrighted images in multimedia information systems and aligns with the broader developments in virtual and augmented realities.
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by jsendak | Feb 16, 2024 | Computer Science
Article Commentary: Exploring the Social Experience of AI-Generated Music
The article explores the question of whether artificial intelligence (AI) can provide a similar social experience as playing music with another person. While AI models, such as large language models, have been successful in generating musical scores, playing music socially involves more than just playing a score. It requires complementing other musicians’ ideas and maintaining proper timing.
In this study, the authors used a neural network architecture called a variational autoencoder trained on a large dataset of digital scores. They adapted this model for a timed call-and-response task with both human and artificial partners. Participants played piano with either a human or AI partner in various configurations and evaluated the performance quality and their first-person experience of self-other integration.
The results of the study showed that while the AI partners showed promise, they were generally rated lower than human partners. However, it is important to note that the artificial partner with the simplest design and highest similarity parameter was not significantly different from human partners on some measures. This suggests that interactive sophistication, rather than just generative capability, is crucial in enabling social AI.
This study highlights the challenges of creating AI systems that can provide a truly social experience in music. While generative models can produce impressive musical scores, they still lack the intuitive understanding and improvisational skills that humans possess. These qualities are essential for successful social interactions in music.
To create more convincing AI partners in music, developers should focus on enhancing the interactive capabilities of these systems. This may involve incorporating real-time feedback mechanisms, responsive improvisation techniques, and adaptive synchronization algorithms. By considering these factors, AI systems could potentially achieve a higher level of integration and collaboration with human musicians.
Furthermore, future research could investigate the impact of different music genres and contexts on the perception of AI-generated music. Different genres may require varying levels of complexity and interaction, and understanding these nuances can help in tailoring AI systems to specific musical domains.
In conclusion, while AI-generated music shows potential, there is still a long way to go in replicating the social experience of playing music with a human partner. By combining generative models with interactive sophistication, researchers can pave the way for more immersive and collaborative musical experiences with AI.
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by jsendak | Feb 15, 2024 | Computer Science
arXiv:2402.07924v1 Announce Type: cross
Abstract: Mixed Reality (MR) and Artificial Intelligence (AI) are increasingly becoming integral parts of our daily lives. Their applications range in fields from healthcare to education to entertainment. MR has opened a new frontier for such fields as well as new methods of enhancing user engagement. In this paper, We propose a new system one that combines the power of Large Language Models (LLMs) and mixed reality (MR) to provide a personalized companion for educational purposes. We present an overview of its structure and components as well tests to measure its performance. We found that our system is better in generating coherent information, however it’s rather limited by the documents provided to it. This interdisciplinary approach aims to provide a better user experience and enhance user engagement. The user can interact with the system through a custom-design smart watch, smart glasses and a mobile app.
Mixed Reality and Artificial Intelligence: Enhancing User Engagement
Mixed Reality (MR) and Artificial Intelligence (AI) are increasingly becoming integral parts of our daily lives, revolutionizing fields like healthcare, education, and entertainment. The combination of these two technologies opens up new frontiers and possibilities for enhancing user engagement and providing personalized experiences.
The focus of this paper is on the development of a new system that combines the power of Large Language Models (LLMs) and mixed reality (MR) to create a personalized companion for educational purposes. This interdisciplinary approach aims to provide a better user experience by leveraging the capabilities of AI and MR technologies.
Leveraging the power of AI, the system is capable of generating coherent and contextually relevant information in response to user inputs or queries. By utilizing Large Language Models, which have been trained on vast amounts of data, the system can provide accurate and helpful information to users, enhancing their learning experience.
The integration of mixed reality into the system adds another layer of immersion and interactivity. Users can interact with the system through a variety of devices, including custom-designed smart watches, smart glasses, and a mobile app. These devices serve as the window into the mixed reality environment, allowing users to see and interact with virtual objects or information seamlessly blended with their real-world surroundings.
The potential applications of this system are vast. In the education sector, it can serve as a personalized tutor or study companion, providing tailored explanations and examples based on the individual’s learning style and progress. In healthcare, it can assist medical professionals during procedures by overlaying real-time information or simulations onto the patient’s body. In entertainment, it can offer immersive experiences and interactive storytelling.
As mentioned in the paper, one limitation of the system is its reliance on the documents provided to it. The quality and diversity of the documents can impact the system’s ability to generate accurate and comprehensive responses. To improve this aspect, future developments could focus on expanding the dataset and refining the pre-training process to increase the system’s knowledge base.
The wider field of multimedia information systems encompasses various technologies and techniques, including animations, artificial reality, augmented reality, and virtual realities. This paper contributes to the advancement of this field by combining AI and MR to create a personalized educational companion. The integration of animations and visualizations within the mixed reality environment can further enhance the learning experience, making complex concepts more understandable and engaging.
In conclusion, the combination of Mixed Reality and Artificial Intelligence holds great potential for enhancing user engagement and providing personalized experiences in various domains. This interdisciplinary approach brings together the fields of multimedia information systems, animations, artificial reality, augmented reality, and virtual realities, paving the way for exciting developments and innovations in the future.
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