Remote sensing (RS) is a rapidly evolving field that facilitates the study of phenomena on the Earth's surface. Through various platforms, including satellites, manned aircraft, and remotely piloted aerial vehicle...
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Remote sensing (RS) is a rapidly evolving field that facilitates the study of phenomena on the Earth's surface. Through various platforms, including satellites, manned aircraft, and remotely piloted aerial vehicles (RPAV), RS has been strategically applied to critical sectors like agriculture and forestry, which are essential for humanity's sustenance. Key applications include crops classification, yield estimation and livestock monitoring and quantification. In the era of artificial intelligence (AI), the development of deep learning (DL) models for such applications often requires extensive field data collection and labor-intensive image labeling, which are both time-consuming and resource-intensive. To address these challenges, this paper presents Procedural Modeling of Rural Environments (PROMORE), a parameterizable, ontology-driven system designed to generate 3D virtual environments encompassing forestry, farmland - mainly focused on vineyards - and village settings. This system also implements functionalities to automate the extraction of training data for deep learning applications in remote sensing, with the declared aim of providing complementary capabilities to data augmentation techniques, encompassing both traditional methods (e.g., flips, rotations, zooming) and advanced approaches such as generative adversarial networks (GANs). By simulating RPAV flights and managing virtual object visibility, PROMORE enables the automatic labeling, delineation, and highlighting of elements of interest (e.g., vine plants, trees, buildings), facilitating the generation of datasets tailored for tasks such as semantic segmentation, and object detection.
Mandalas, intricate artistic designs with radial symmetry, are imbued with a timeless allure that transcends cultural boundaries. Found in various cultures and spiritual traditions worldwide, mandalas hold profound si...
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Mandalas, intricate artistic designs with radial symmetry, are imbued with a timeless allure that transcends cultural boundaries. Found in various cultures and spiritual traditions worldwide, mandalas hold profound significance as symbols of unity, wholeness, and spiritual transformation. At the heart of mandalas lies the concept of sacred symmetry, a timeless principle that resonates with the deepest realms of human consciousness. However, in handcrafted mandalas, symmetry often falls short of perfection, necessitating refinement to evoke harmony and balance. With this in mind, we introduce a computational approach aimed at capturing the all-round symmetry of mandalas through minimalist principles. By leveraging innovative geometric and graph-theoretic tools and an interactive twin atlas, this approach streamlines parameter domains to achieve the revered state of sacred symmetry, epitomizing harmonious balance. This is especially beneficial when dealing with handcrafted mandalas of subpar quality, necessitating concise representations for tasks like mandala editing, recreation, atlas building, and referencing. Experimental findings and related results demonstrate the effectiveness of the proposed methodology.
Real-time walk through very large and detailed scenes is a challenge for both content design, data management, and rendering, and requires LOD to handle the scale range. In the case of partly stochastic content (cloud...
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Real-time walk through very large and detailed scenes is a challenge for both content design, data management, and rendering, and requires LOD to handle the scale range. In the case of partly stochastic content (clouds, cosmic dust, fire, terrains, etc.), proceduralism allows arbitrary large and detailed scenes with no or little storage and offers embedded LOD, but the rendering gets even costlier. In this paper, we propose to boost the performance of Fractional Brownian Motion (FBM)-based noise rendering (e.g., 3D Perlin noise, hypertextures) in two ways: improving the stepping efficiency of Sphere Tracing of general Signed Distance Functions (SDF) considering the first and second derivatives, and treating cascaded sums such as FBM as nested bounding volumes. We illustrate this on various scenes made of either opaque material, constant semi-transparent material, or non-constant (i.e.,full volumetric inside) material, including animated content - thanks to on-the-fly proceduralism. We obtain real-time performances with speedups up to 12-folds on opaque or constant semi-transparent scenes compared to classical Sphere tracing, and up to 2-folds (through empty space skipping optimization) on non-constant density volumetric scenes.
In the current field of speech-driven 3D facial animation, transformer-based methods are limited in practical applications due to their high computational complexity. A new model-NewTalker-is proposed, which has core ...
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In the current field of speech-driven 3D facial animation, transformer-based methods are limited in practical applications due to their high computational complexity. A new model-NewTalker-is proposed, which has core modules consisting of the residual bidirectional Mamba (RBM) and the time-frequency domain Kolmogorov-Arnold networks (TFK). The RBM module incorporates the philosophy of Mamba, enhancing the model's predictive ability for sequence data by utilizing both past and future contextual information, thereby reducing the computational complexity. The TFK module integrates the temporal and frequency domain information of audio data through Kolmogorov-Arnold networks, allowing the model to generate 3D facial animations smoothly while learning more detailed features. Extensive experiments and user studies have shown that the proposed NewTalker significantly surpasses current mainstream algorithms in terms of animation quality and inference speed, achieving the state-of-the-art level in this domain.
Sparse view 3D reconstruction remains challenging due to inherent data scale limitations. Mainstream sparse view 3D reconstruction algorithms based on the NeRF framework struggle to balance generation quality and real...
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Sparse view 3D reconstruction remains challenging due to inherent data scale limitations. Mainstream sparse view 3D reconstruction algorithms based on the NeRF framework struggle to balance generation quality and real-time performance. Recently, the advent of 3D Gaussian Splatting technology has demonstrated remarkable results, becoming increasingly prominent in 3D scene representation and reconstruction. Exploring the application of 3D Gaussian Splatting technology for sparse view 3D reconstruction represents a promising research avenue. Based on this, our paper provides a comprehensive review of current sparse view 3D reconstruction methods leveraging 3D Gaussian Splatting, with an emphasis on extracting effective reconstruction information from input images and utilizing these data to generate realistic scenes efficiently and reliably. We then provide a detailed discussion on how the algorithm addresses issues such as artifacts and scale ambiguous, which are common challenges in this field. In the subsequent sections, we present both quantitative and qualitative comparisons of various sparse-view 3D reconstruction methods, roughly demonstrating the advantages of sparse view 3D Gaussian splatting methods in terms of reconstruction quality and efficiency. Furthermore, we analyze the potential applications of sparse view 3D Gaussian splatting methods. Finally, we identify the challenges faced by sparse-view 3D Gaussian splatting reconstruction and suggest potential solutions. We hope that our analysis will provide valuable insights for future research efforts.
Material appearance acquisition allows researchers to capture the optical properties of surfaces and use them in different tasks such as material analysis, digital twins reproduction, 3D configurators, augmented and v...
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Material appearance acquisition allows researchers to capture the optical properties of surfaces and use them in different tasks such as material analysis, digital twins reproduction, 3D configurators, augmented and virtual reality, etc. Precise acquisition of such properties requires complex and expensive hardware. In this paper, we aim to answer the following research challenge: Can we design an accurate enough but low-cost and portable device for material appearance acquisition? We present the rationale behind the design of our device using consumer-grade hardware components. Ultimately, our device costs EUR 80 and can acquire surface patches of size 5 x 5 cm with a 40 pix/mm resolution. Our device exploits a traditional RGB camera to capture a surface using 24 different images, each photographed using different lighting conditions. The different lighting conditions are generated by exploiting the LED rings included in our device;specifically, each of the 24 images is acquired by turning on one individual LED at time. We also illustrate the custom processing pipelines developed to support capturing and generating the material data in terms of albedo, normal, and roughness maps. The accuracy of the acquisition process is comprehensively evaluated both quantitatively and qualitatively. Results show that our low-cost device can faithfully acquire different materials. The usefulness of our device is further demonstrated by a textile virtual catalog application that we designed for rendering virtual fabrics on a mobile apparatus.
computer graphics (CG) advancements have allowed the creation of more realistic Virtual Humans (VH) through modern techniques for animating the VH body and face, thereby affecting perception. From traditional methods,...
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computer graphics (CG) advancements have allowed the creation of more realistic Virtual Humans (VH) through modern techniques for animating the VH body and face, thereby affecting perception. From traditional methods, including blend shapes, to driven animations using facial and body tracking, these advancements can potentially enhance the perception of comfort and realism in relation to VHs. Previously, Psychology studied facial movements in humans, with some works separating expressions into macro and micro expressions. Also, some previous CG studies have analyzed how macro and micro expressions are perceived, replicating psychology studies in VHs, encompassing studies with realistic and cartoon VHs, and exploring different VH technologies. However, instead of using facial tracking animation methods, these previous studies animated the VHs using blendshapes interpolation. To understand how the facial tracking technique alters the perception of VHs, this paper extends the study to macro and micro expressions, employing two datasets to transfer real facial expressions to VHs and analyze how their expressions are perceived. Our findings suggest that transferring facial expressions from real actors to VHs significantly diminishes the accuracy of emotion perception compared to VH facial animations created by artists.
Finding surface loops around narrow sections of a surface is widely used as a prepossessing step in various applications such as segmentation, shape analysis, path planning, and robotics. A common approach to locating...
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Finding surface loops around narrow sections of a surface is widely used as a prepossessing step in various applications such as segmentation, shape analysis, path planning, and robotics. A common approach to locating such loops is based on surface topology. However, such geodesic loops also exist on topologically trivial genus-0 surfaces, where all such loops can continuously deform to a point. While a few existing 3D geometry-aware topological approaches may succeed in detecting such additional narrow loops, their construction can be cumbersome. To extend beyond the limitations of topologically nontrivial independent loops while remaining efficient, we propose a novel approach that leverages the shape's skeleton for computing surface loops of handle or tunnel type. Given a closed surface mesh, our algorithm produces a practically comprehensive set of loops encircling narrow regions of the volume inside or outside the surface. Notably, our approach streamlines and expedites computations by accepting a skeleton, a 1D representation of the shape, as part of the input. Specifically, handle-type loops are discovered by examining a small subset of the skeleton points as candidate loop centers, while tunnel-type loops are identified by examining only the high-valence skeleton points.
Existing masked image modeling (MIM) methods mainly fill and enhance images by modeling and filling masked areas. These techniques usually borrow principles from computer graphics, where similar methods are used to sy...
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Existing masked image modeling (MIM) methods mainly fill and enhance images by modeling and filling masked areas. These techniques usually borrow principles from computer graphics, where similar methods are used to synthesize missing parts of images or meshes. However, current MIM methods still have problems such as incomplete capture of local information and failure to capture dynamic information. To address the above situation, we propose a multi-mask autoencoder (M-MAE). M-MAE borrows the smooth transition technology from computer graphics, combines patch masking and random masking, and enhances the stability of the model by optimizing the processing of masked areas during training. In addition, we introduce a scaling layer (LScale) to improve training dynamics, similar to the scaling and distortion transformations used in graphics to adapt to different spatial distributions. To further improve the accuracy of the model in capturing spatial relationships, we propose a position encoding offset method that can generate more spatially aware encodings, thereby effectively enhancing the spatial expression ability of the model. Comparative experiments show that M-MAE can achieve an Acc1 of 84.5 on the ImageNet-1K dataset, an Acc1 of 58.2 on the Places365 dataset, and an mIoU of 49.4 on the ADE20K dataset. From the experimental results, it can be seen that our innovation improves the performance of the model in multiple visual tasks and provides a tighter integration between visual and graphics methods. Code is released at (https://***/zoomba35/mmae).
Virtual reality enables new approaches to teaching various learning content. However, the development of learning environments is complex and there are only a few guidelines that can be used in the development of VR l...
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ISBN:
(纸本)9783031426810;9783031426827
Virtual reality enables new approaches to teaching various learning content. However, the development of learning environments is complex and there are only a few guidelines that can be used in the development of VR learning environments. This paper addresses this gap and presents the evaluation of a computer science education simulation. The questionnaire of the UXIVE model, combined with feedback analysed with systematic, rule-guided qualitative text analysis, was used to analyse the influence of user experience components. The result is a concept to transfer usability outcomes in a structured way into best practices and conditions for success.
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