Distributed ray tracing algorithms are widely used when rendering massive scenes, where data utilization and load balancing are the keys to improving performance. One essential observation is that rays are temporally ...
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Distributed ray tracing algorithms are widely used when rendering massive scenes, where data utilization and load balancing are the keys to improving performance. One essential observation is that rays are temporally coherent, which indicates that temporal information can be used to improve computational efficiency. In this paper, we use temporal coherence to optimize the performance of distributed ray tracing. First, we propose a temporal coherence-based scheduling algorithm to guide the task/data assignment and scheduling. Then, we propose a virtual portal structure to predict the radiance of rays based on the previous frame, and send the rays with low radiance to a precomputed simplified model for further tracing, which can dramatically reduce the traversal complexity and the overhead of network data transmission. The approach was validated on scenes of sizes up to 355 GB. Our algorithm can achieve a speedup of up to 81% compared to previous algorithms, with a very small mean squared error.
To address the significant challenges of high false positive and false negative rates in existing algorithms for detecting cervical fluid-based cells, an enhanced Yolov5s network is introduced. This paper details a no...
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To address the significant challenges of high false positive and false negative rates in existing algorithms for detecting cervical fluid-based cells, an enhanced Yolov5s network is introduced. This paper details a novel approach that dynamically adjusts the weights of channels and the spatial attention in modules, substantially improving feature extraction from small objects and boosting the detection capabilities of the network. Furthermore, Mixup data augmentation technology is incorporated to counter the issue of imbalanced data categories in the custom dataset. The Complete Intersection over Union loss function is also employed to refine coordinate localization accuracy during training. Tested on the proprietary cervical cytology dataset, the modified Yolov5s achieves a mean Average Precision of 92.1%, surpassing the previous state-of-the-art by 5.6%. This enhancement substantiates the efficacy of the proposed model. Code and models are accessible at .
Edge-aware image smoothing refers to the removal of details with edges preserved. It is an essential topic in the field of image processing and computer graphics. In this paper, in order to achieve better edge preserv...
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Edge-aware image smoothing refers to the removal of details with edges preserved. It is an essential topic in the field of image processing and computer graphics. In this paper, in order to achieve better edge preservation than the existing models, we propose a robust edge-preserving image filtering method based on a complementary weighting scheme. Both isotropic and anisotropic weights are involved in our model to adapt the fidelity and the regularization terms. To efficiently solve the proposed model, we introduce an effective algorithm based on additive half quadratic minimization, alternating direction of multipliers, and Fourier domain optimization strategies. We experimentally validate the proposed filter on several low-level vision tasks. Both quantitative and qualitative experimental results show significant superiority of our proposed filter compared to existing techniques. Furthermore, the filter exhibits high efficiency and is able to process 720P color images (over 10 fps) in real-time on an NVIDIA RTX 3070. Therefore, it is practical for real-world applications.
Structure from Motion (SfM) is a computer vision technique used to reconstruct three-dimensional (3D) structures from a series of two-dimensional (2D) images or video frames. However, SfM tools struggle with transpare...
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Structure from Motion (SfM) is a computer vision technique used to reconstruct three-dimensional (3D) structures from a series of two-dimensional (2D) images or video frames. However, SfM tools struggle with transparent objects, reflective surfaces, and low-resolution frames. In such situations, image-based interactive 3D modeling software packages are employed to model 3D objects and measure dimensions. Our contributions to this work are twofold. First, we have introduced new tools to improve 3D modeling software packages;such tools are aimed at easing the workload for users. Second, we have conducted a comprehensive user study to evaluate the efficacy of popular 3d modeling software packages. The task is to measure certain dimensions for which ground truth measurements are already known. A relative error is calculated for every measurement. The evaluation of each software tool is done through survey form, event logs, and measurement relative error. The results of this user study clearly show that our approach to 3D modeling using multiple images has a lower relative error and produces higher quality 3D models than other software packages. In addition, it shows our new tools reduce the required time for completing a task.
Rubber trees in coastal habitats are exposed to a high degree of wind stress. An algorithm-hardware synergetic methodology was developed for investigating and predicting rubber tree phenotyping excited by strong winds...
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Rubber trees in coastal habitats are exposed to a high degree of wind stress. An algorithm-hardware synergetic methodology was developed for investigating and predicting rubber tree phenotyping excited by strong winds. The framework includes (1) a custom-designed industrial fan that recreates a variable airflow field at wind speeds of 15, 30 and 45 m/s coupled with a terrestrial laser scanner and bundled motion sensors to acquire point clouds and vibration data;(2) a graphic model that approximates tree canopies based on foliage clumps with phenotypic traits that are derived from point clouds captured while trees are subjected to aerodynamic drag;and (3) the wind characteristic parameters of forest canopies were calculated by a developed forest-specialized k-epsilon turbulence model combining the constructed tree models and grid-scale subdivision of the wind fluid field. (4) A digital twin model that incorporates detailed tree phenotypic traits and considers plant mechanical characteristics was established, depicting the related wind-induced actions of target trees under various wind influences. The results show that tree crowns with spreading forms are prone to yield larger pendulum amplitudes than compact crowns, but trees directly exposed to wind exhibit greater crown volume reductions than trees in sheltered areas. Within tree canopies, a one-fold increase in inlet wind speed intensified crown compression (approximately 17 % decrease in crown volume), generated 2.1-fold pressure gradients and increased turbulence kinetic energy by approximately 60 %. Moreover, the entire scenario of the adaptation of experimental trees to wind perturbations was visually restored using digital twin techniques, serving as an integral behaviour dataset for further data-driven decision-making. In summary, this paper presents a comprehensive methodology that can decipher the phenotypic manifestations of trees' reactions to wind hazards, with potential applications in phenotyping or e
This special section contains three papers, which are extended contributions of original works presented at the 25th SIBGRAPI -Conference on graphics, Patterns and Images. Started in 1988, SIBGRAPI has been the main s...
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This special section contains three papers, which are extended contributions of original works presented at the 25th SIBGRAPI -Conference on graphics, Patterns and Images. Started in 1988, SIBGRAPI has been the main scientific event in computer graphics, Image Processing and related areas in Brazil. In 2012, celebrating the 25th anniversary of SIBGRAPI, it was held in the historical city of Ouro Preto, Minas Gerais. Each year, best papers are selected and authors are invited to submit extended versions to high quality journals. After a rigorous peer-reviewing process, the three contributions published in this section were selected among four invited submissions to be published in computers & graphics.
Quantum computing is emerging as a transformative force in computer science, offering significant advantages in speed and efficiency over classical computing methods. Despite this promise, the practical application of...
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Quantum computing is emerging as a transformative force in computer science, offering significant advantages in speed and efficiency over classical computing methods. Despite this promise, the practical application of quantum computing to visual computing faces numerous challenges, including the complexity of quantum algorithms and the limitations of current quantum hardware. These challenges underscore the necessity for focused research and collaboration in this interdisciplinary area. This Special Issue of IEEE computer graphics and Applications, "Quantum Visual Computing," aims at drawing attention to these challenges and bringing together pioneering research at the intersection of quantum and visual computing. By fostering dialogue and innovation between these fields, we hope to inspire new solutions and advance the state of the art in both domains.
This special issue of the IEEE Transactions on Visualization and computer graphics (TVCG) serves as the journal proceedings of the IEEE Pacific Visualization Conference 2024, held on April 23–26, 2024, in Tokyo, Japa...
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This special issue of the IEEE Transactions on Visualization and computer graphics (TVCG) serves as the journal proceedings of the IEEE Pacific Visualization Conference 2024, held on April 23–26, 2024, in Tokyo, Japan. The General Chair was Issei Fujishiro from Keio University.
The study of visual communication and its role in conveying information through visual elements is crucial in aiding the comprehension of complex concepts. computer imaging involves installing an operating system (OS)...
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The study of visual communication and its role in conveying information through visual elements is crucial in aiding the comprehension of complex concepts. computer imaging involves installing an operating system (OS), applications, and settings on new devices, with cloud-based methods streamlining the process and reducing overhead. As modern society becomes more reliant on digital technology, the complexity of information systems continues to grow, further emphasizing the importance of computer technology. This paper focuses on the integration of computer imaging technology and visual communication approaches. The proposed image processing system has been widely adopted and is now considered a key component of advanced, practical research. The importance of computer graphics in enhancing the quality and impact of visual communication has been fully acknowledged. Works produced using modern graphic image processing techniques have the potential to significantly influence viewers' perceptions. The study explores the impact of computer graphics and image technology on the development of visual communication, providing valuable data for innovative city applications. Additionally, the paper delves into the critical role of computer graphics and image technology in realizing various aspects of visual communication prototypes. For performance analysis, quality metrics such as Mean Square Error (MSE), Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), and Contrast-to-Noise Ratio (CNR) are utilized, along with reliability metrics like Accuracy, Precision, Recall, and F1-Score. The proposed approach achieves superior efficiency compared to other methods. The performance results include MSE of 13%, PSNR of 40 dB, SSIM of 0.72, CNR of 39 dB, Accuracy of 98.76%, Precision of 98.64%, Recall of 97.56%, and an F1-Score of 97.87%.
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