This study explored the utilization of digital technology in public art design for urban landscapes, focusing on CAD and computer graphics to create dynamic and interactive installations. The research presented a desi...
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This study explored the utilization of digital technology in public art design for urban landscapes, focusing on CAD and computer graphics to create dynamic and interactive installations. The research presented a design approach aligned with contemporary design practices by summarizing the attributes of public art and emphasizing the use of curve constraint forms. Advanced parametric design techniques significantly reduced the development time of 3D patterns from 30 h to just 10 h, demonstrating enhanced efficacy and precision. Innovative curve sampling techniques, including iso-parametric and isoarc length methods, resulted in a 25% improvement in the smoothness and continuity of design curves compared to traditional techniques. The public art installations developed in this study were designed to reflect and celebrate the cultural and historical aspects of urban areas, fostering a stronger connection between residents and their environment. Surveys conducted with 200 participants revealed that 85% felt a deeper connection to their cultural heritage due to the installations. The interactive nature of these art pieces engaged the public through visual, tactile, and behavioral interactions, significantly enhancing the aesthetic and functional quality of urban spaces. Despite these successes, the study identified several limitations, including a scarcity of authoritative literature and a lack of comprehensive case analyses for large-scale implementation. These gaps suggest the need for further investigation to explore the long-term feasibility and sustainability of digital public art installations. Future studies should investigate the durability, maintenance costs, and environmental impact of these installations, as well as promote interdisciplinary collaboration to develop new materials and technologies. Overall, this research highlighted the transformative potential of digital technology in public art design, offering practical insights and techniques for creating
Most existing multi-view stereo (MVS) methods fail to consider global context information in the stage of feature extraction and cost aggregation. As transformers have shown remarkable performance on various vision ta...
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Most existing multi-view stereo (MVS) methods fail to consider global context information in the stage of feature extraction and cost aggregation. As transformers have shown remarkable performance on various vision tasks due to their ability to perceive global contextual information, this paper proposes a transformer-based feature enhancement network (TF-MVSNet) to facilitate feature representation learning by combining local features (both 2D and 3D) with long-range contextual information. To reduce memory consumption of feature matching, the cross-attention mechanism is leveraged to efficiently construct 3D cost volumes under the epipolar constraint. Additionally, a colour-guided network is designed to refine depth maps at a coarse stage, hence reducing incorrect depth predictions at a fine stage. Extensive experiments were performed on the DTU dataset and Tanks and Temples (T&T) benchmark and results are reported. (1) We introduce Vision Transformers to enhance both 2D feature representations and global 3D spatial information aggregation. (2) We design a color-guided network to refine depth maps. (3) Proposed method achieves competitive performance on both DTU dataset and Tanks and Temples benchmark. image
Approximate convex decomposition simplifies complex shapes into manageable convex components. In this work, we propose a novel surface-based method that achieves efficient computation times and sufficiently convex res...
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Approximate convex decomposition simplifies complex shapes into manageable convex components. In this work, we propose a novel surface-based method that achieves efficient computation times and sufficiently convex results while avoiding overapproximation of the input model. We start approximation using mesh simplification. Then we iterate over the surface polygons of the mesh and divide them into convex groups. We utilize planar and angular equations to determine suitable neighboring polygons for inclusion in forming convex groups. To ensure our method outputs a sufficient result for a wide range of input shapes, we run multiple iterations of our algorithm using varying planar thresholds and mesh simplification levels. For each level of simplification, we find the planar threshold that leads to the decomposition with the least number of pieces while remaining under a certain concavity threshold. Subsequently, we find the simplification level that houses the decomposition with the least concavity, and output that decomposition as our result. We demonstrated experiment results that show the stability of our method as well as compared our work to two convex decomposition algorithms, providing discussion on the shortcomings and advantages of the proposed method. Notably, our main advantage turns out to be on time efficiency as we produce output faster than our competitors which, however, outperform our results for some models from an accuracy perspective.
How we perceive and experience the world around us is inherently multisensory. Most of the Virtual Reality (VR) literature is based on the senses of sight and hearing. However, there is a lot of potential for integrat...
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How we perceive and experience the world around us is inherently multisensory. Most of the Virtual Reality (VR) literature is based on the senses of sight and hearing. However, there is a lot of potential for integrating additional stimuli into Virtual Environments (VEs), especially in a training context. Identifying the relevant stimuli for obtaining a virtual experience that is perceptually equivalent to a real experience will lead users to behave the same across environments, which adds substantial value for several training areas, such as firefighters. In this article, we present an experiment aiming to assess the impact of different sensory stimuli on stress, fatigue, cybersickness, Presence and knowledge transfer of users during a firefighter training VE. The results suggested that the stimulus that significantly impacted the user's response was wearing a firefighter's uniform and combining all sensory stimuli under study: heat, weight, uniform, and mask. The results also showed that the VE did not induce cybersickness and that it was successful in the task of transferring knowledge.
Humans constantly interact with objects to accomplish tasks. To understand such interactions, computers need to reconstruct these in 3D from images of whole bodies manipulating objects, e.g., for grasping, moving and ...
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Humans constantly interact with objects to accomplish tasks. To understand such interactions, computers need to reconstruct these in 3D from images of whole bodies manipulating objects, e.g., for grasping, moving and using the latter. This involves key challenges, such as occlusion between the body and objects, motion blur, depth ambiguities, and the low image resolution of hands and graspable object parts. To make the problem tractable, the community has followed a divide-and-conquer approach, focusing either only on interacting hands, ignoring the body, or on interacting bodies, ignoring the hands. However, these are only parts of the problem. On the contrary, recent work focuses on the whole problem. The GRAB dataset addresses whole-body interaction with dexterous hands but captures motion via markers and lacks video, while the BEHAVE dataset captures video of body-object interaction but lacks hand detail. We address the limitations of prior work with InterCap, a novel method that reconstructs interacting whole-bodies and objects from multi-view RGB-D data, using the parametric whole-body SMPL-X model and known object meshes. To tackle the above challenges, InterCap uses two key observations: (i) Contact between the body and object can be used to improve the pose estimation of both. (ii) Consumer-level Azure Kinect cameras let us set up a simple and flexible multi-view RGB-D system for reducing occlusions, with spatially calibrated and temporally synchronized cameras. With our InterCap method we capture the InterCap dataset, which contains 10 subjects (5 males and 5 females) interacting with 10 daily objects of various sizes and affordances, including contact with the hands or feet. To this end, we introduce a new data-driven hand motion prior, as well as explore simple ways for automatic contact detection based on 2D and 3D cues. In total, InterCap has 223 RGB-D videos, resulting in 67,357 multi-view frames, each containing 6 RGB-D images, paired with pseudo gro
Kinematic tracking of native anatomy in dynamic radiography facilitates understanding of in vivo movement. Tracking is performed using model-image registration, which involves estimating 6 degree-of-freedom poses of a...
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Kinematic tracking of native anatomy in dynamic radiography facilitates understanding of in vivo movement. Tracking is performed using model-image registration, which involves estimating 6 degree-of-freedom poses of anatomic structures by comparing captured radiographs to dynamically rendered images of digital models. This procedure can produce accurate pose estimates of native anatomy, but computational efficiency remains a concern. A key source of latency in model-image registration is the iterative rendering of digitally reconstructed radiographs, required for evaluation of candidate poses. This technical note introduces an efficient algorithm for rendering digitally reconstructed radiographs. The proposed method is shown to accelerate rendering speeds by up to 50% compared to a baseline method which is commonly used in registration frameworks. Efficient rendering of digitally reconstructed radiographs may enhance the overall viability of model-image registration for use in kinematic tracking, and may contribute to bringing this technology closer to adoption in clinical settings.
Three-dimensional mesh compression is vital to support advances in many scenarios, such as 3D web-based applications. Existing 3D mesh methods usually require complex data structures and time-consuming processing. Giv...
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Three-dimensional mesh compression is vital to support advances in many scenarios, such as 3D web-based applications. Existing 3D mesh methods usually require complex data structures and time-consuming processing. Given a mesh represented by its vertices and triangular faces, we present a novel, fast, and straightforward encoding algorithm. Our method encodes the mesh connectivity data based on an upper triangular matrix which is easily recovered by its underlying decoding process. Our technique encodes the mesh edges in linear time without losing any face in the process. Results show that our method provides a connectivity compression rate of 55.29 and an average total compression rate of 27.09. Furthermore, our approach achieves, on average, a similar compressing rate of state-of-the-art algorithms, such as OpenCTM, which considers geometry and connectivity, while our approach considers only their connectivity.
The polygonal contact model is an established contact algorithm for multibody dynamics based on polygonal surfaces. Some guidance for its practical use is presented. In particular, assignment and discretization of the...
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The polygonal contact model is an established contact algorithm for multibody dynamics based on polygonal surfaces. Some guidance for its practical use is presented. In particular, assignment and discretization of the surface meshes are discussed with regard to correct results and optimal efficiency. Moreover, notes on stiffness and damping parameters are *** improved implementation of the polygonal contact model is introduced. The new algorithm goes without quite complicated intersection construction steps. As a consequence, it is less complex, more robust and usually more efficient than the classic *** examples of varied complexity demonstrate both notes on usage and improved implementation of the polygonal contact model.
This article introduces a new method for simulating synthetic aperture sonar (SAS) raw coherent echo data, which is orders of magnitude faster than the commonly used point and facet diffraction models. The new approac...
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This article introduces a new method for simulating synthetic aperture sonar (SAS) raw coherent echo data, which is orders of magnitude faster than the commonly used point and facet diffraction models. The new approach uses Fourier wavefield generation and propagation in combination with a highly optimized optical rendering engine. It has been shown to produce a quantifiably similar quality of data and data products (i.e., images and spectra) to a point-diffraction model, capturing the important coherent wave physics (including diffraction, speckle, aspect-dependence, and layover) as well as effects of the SAS processing chain (including image focusing errors and artifacts). This new simulation capability may be an enabler for augmenting data sets with physically accurate and diverse synthetic data for robust machine learning.
This study aimed to evaluate the performance of three artificial intelligence (AI) image synthesis models, Dall-E 2, Stable Diffusion, and Midjourney, in generating urban design imagery based on scene descriptions. A ...
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This study aimed to evaluate the performance of three artificial intelligence (AI) image synthesis models, Dall-E 2, Stable Diffusion, and Midjourney, in generating urban design imagery based on scene descriptions. A total of 240 images were generated and evaluated by two independent professional evaluators using an adapted sensibleness and specificity average metric. The results showed significant differences between the three AI models, as well as differing scores across urban scenes, suggesting that some projects and design elements may be more challenging for AI art generators to represent visually. Analysis of individual design elements showed high accuracy in common features like skyscrapers and lawns, but less frequency in depicting unique elements such as sculptures and transit stops. AI-generated urban designs have potential applications in the early stages of exploration when rapid ideation and visual brainstorming are key. Future research could broaden the style range and include more diverse evaluative metrics. The study aims to guide the development of AI models for more nuanced and inclusive urban design applications, enhancing tools for architects and urban planners.
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