When considering sparse motion capture marker data, one typically struggles to balance its overfitting via a high dimensional blendshape system versus underfitting caused by smoothness constraints. With the current tr...
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When considering sparse motion capture marker data, one typically struggles to balance its overfitting via a high dimensional blendshape system versus underfitting caused by smoothness constraints. With the current trend towards using more and more data, our aim is not to fit the motion capture markers with a parameterized (blendshape) model or to smoothly interpolate a surface through the marker positions, but rather to find an instance in the high resolution dataset that contains local geometry to fit each marker. Just as is true for typical machine learning applications, this approach benefits from a plethora of data, and thus we also consider augmenting the dataset via specially designed physical simulations that target the high resolution dataset such that the simulation output lies on the same so-called manifold as the data targeted.
Exploring topologically distinctive trajectories provides more options for robot motion planning. Since computing time grows greatly with environment complexity, improving exploration efficiency and picking the optima...
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Exploring topologically distinctive trajectories provides more options for robot motion planning. Since computing time grows greatly with environment complexity, improving exploration efficiency and picking the optimal trajectory in complex environments are critical issues. To this end, this paper proposes a Graphic-and Timed-Elastic-Band-based approach (GraphicTEB) with spatial completeness and high computing efficiency. The environment is analyzed utilizing computer graphics, where obstacles are extracted as nodes and their relationships are built as edges. Three contributions are presented. 1) By assembling directed detours formed by nodes and segmented paths formed by edges, a generalized path consisting of nodes and edges derives various normal paths efficiently. 2) By multiplying two vectors starting from the obstacle point closest to the waypoint and the boundary point farthest from the waypoint, an novel obstacle gradient is introduced to guide safer optimization. 3) By assigning edges with asymmetric Gaussian model, a trajectory evaluation strategy is designed to reflect the motion tendency and motion uncertainty of dynamic obstacles. Qualitative and quantitative simulations demonstrate that the proposed GraphicTEB achieves spatial completeness, higher scene pass rate, and fastest computing efficiency. Experiments are implemented in long corridor and broad room scenarios, where the robot goes through gaps safely, finds trajectories quickly, and passes pedestrians politely Note to Practitioners-The motivation stems from the fact that our daily cruising robot occasionally gets trapped in a corridor with piled obstacles or in a complex dynamic crowd due to the lack of a reliable trajectory. The solution is to search for more topologically distinctive trajectories and pick the optimal one. Considering that existing open-source approaches are either incomplete or highly time-consuming, a method for clustering and searching trajectories in the obstacle-occupied r
In recent years, most video segmentation methods use deep CNN to process the input image, but they did not fully mine the rich intermediate predictions in spatio-temporal space. And, the segmentation challenges such a...
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In recent years, most video segmentation methods use deep CNN to process the input image, but they did not fully mine the rich intermediate predictions in spatio-temporal space. And, the segmentation challenges such as occlusion, severe deformation and illumination have not been well solved so far. To alleviate these problems, this paper focuses on constructing multi module network structures that represent multi semantics and proposes a video object segmentation network via coupled-stream architecture with feature memory mechanism. This network first extracts high-level semantic features, edge features, long-term and short-term stable depth features of the target, and then decode them into the segmentation mask of target. In addition, negative skeleton inhibition and frame interpolation are used to prevent the interference of similar objects and motion blur, respectively. The method has a low GPU memory usage, regardless of the number of object in video. And performs 86.5%and 62.4% in J&F measure on DAVIS 2016 and DAVIS 2017 validation set, without fine-tuning and online training. This paper focuses on constructing multi module network structures that represent multi semantics and proposes a video object segmentation network via coupled-stream architecture with feature memory mechanism. image
IEEE computer graphics and Applications began publishing "Applications" as a regular department under its present editor 30 years ago in November 1994, with the goal of featuring interesting examples of usin...
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IEEE computer graphics and Applications began publishing "Applications" as a regular department under its present editor 30 years ago in November 1994, with the goal of featuring interesting examples of using computer graphics to solve real-world problems. The Applications department has appeared in every issue since, making the present article the 181st such article to appear. To mark this occasion, the Applications department takes a look back by revisiting the most cited articles that have appeared since the department's inception.
This paper proposes a projection system that optically removes the cast shadow in projection mapping. Specifically, we realize the large-aperture (LA) projection using a large-format Fresnel lens to suppress cast shad...
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This paper proposes a projection system that optically removes the cast shadow in projection mapping. Specifically, we realize the large-aperture (LA) projection using a large-format Fresnel lens to suppress cast shadows by condensing the projection light from a wide viewing angle. However, the resolution and contrast of the projected results are significantly degraded by defocus blur, veiling glare, and stray light caused by the aberration of an LA Fresnel lens. To solve the technical problems, we employ two different approaches: optical and digital image processing methods. First, we introduce a residual projector with a typical aperture lens on the same optical axis as the LA projector, projecting the residual (i.e., high-frequency) components attenuated in the LA projection. These projectors play different roles in shadow suppression and blur compensation, both achieved by projecting simultaneously. Secondly, we optimize the pair of projection images that can balance the shadow suppression and deblurring performance of our projection system. We implemented a proof-of-concept prototype and validated the above-mentioned techniques through projection experiments and a user study.
We introduce a new representation of recently introduced perturbed Bernstein operators BnM$$ {B}_n circumflex M $$ in terms of classical Bernstein operators. Using this new representation, we investigate the shape-pre...
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We introduce a new representation of recently introduced perturbed Bernstein operators BnM$$ {B}_n circumflex M $$ in terms of classical Bernstein operators. Using this new representation, we investigate the shape-preserving properties of the operator BnM$$ {B}_n circumflex M $$. In particular, we prove that perturbed Bernstein operators preserve monotonicity and convexity of functions for certain cases. On the other hand, we demonstrate with some counterexamples that monotonicity and convexity preserving properties fail in other cases. Moreover, we present some weaker results in these cases.
University of Stuttgart educators have updated three computer science courses to incorporate forward-compatible OpenGL. To help students, they developed an educational framework that abstracts some of modern OpenGL...
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University of Stuttgart educators have updated three computer science courses to incorporate forward-compatible OpenGL. To help students, they developed an educational framework that abstracts some of modern OpenGL's difficult aspects.
The advantages of Virtual Reality (VR) over traditional training, together with the development of VR technology, have contributed to an increase in the body of literature on training professionals with VR. However, t...
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The advantages of Virtual Reality (VR) over traditional training, together with the development of VR technology, have contributed to an increase in the body of literature on training professionals with VR. However, there is a gap in the literature concerning the comparison of training in a Virtual Environment (VE) with the same training in a Real Environment (RE), which would contribute to a better understanding of the capabilities of VR in training. This paper presents a study with firefighters (N = 12) where the effect of a firefighter training exercise in a VE was evaluated and compared to that of the same exercise in a RE. The effect of environments was evaluated using psychophysiological measures by evaluating the perception of stress and fatigue, transfer of knowledge, sense of presence, cybersickness, and the actual stress measured through participants' Heart Rate Variability (HRV). The results showed a similar perception of stress and fatigue between the two environments;a positive, although not significant, effect of the VE on the transfer of knowledge;the display of moderately high presence values in the VE;the ability of the VE not to cause symptoms of cybersickness;and finally, obtaining signs of stress in participants' HRV in the RE and, to a lesser extent, signs of stress in the VE. Although the effect of the VE was shown to be non-comparable to that of the RE, the authors consider the results encouraging and discuss some key factors that should be addressed in the future to improve the results of the training VE.
The denoising of images is an important research direction in computer vision. We consider the image denoising task as an estimation problem of the filtering policy related to image features, which is different from e...
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The denoising of images is an important research direction in computer vision. We consider the image denoising task as an estimation problem of the filtering policy related to image features, which is different from end-to-end image mapping. Commonly used simple filters such as gaussian filtering and bilateral filtering have fixed global denoising policies. However, the denoising policies of different filters can only adapt to limited image features. To solve this problem, we propose a method that applies different filters to different spatial ranges and adjusts the parameters of these filters simultaneously. Since not all filters can be easily transformed into differentiable forms and it is difficult to obtain paired datasets of filter action areas, we use reinforcement learning (RL) methods to estimate the spatial domain action range and adjustable parameters of filters, respectively. Furthermore, for removing higher intensity noise, simple filters can iteratively approximate higher-order denoising policies and obtain more accurate and stable denoising results with the increase of iteration steps. Experimental results show that our proposed method can not only generate intuitive and interpretable denoising policies but also achieve comparable or better visual effects and computational efficiency than baseline methods. (1) Selection of filter parameters for image denoising using reinforcement learning. (2) Increased solution space range compared to using discrete action space. (3) The use of filters improves the interpretability of the denoising process. (4) Show the range of filters and the parameter selection for each ***
The primary objective of this work is to explore various approximation properties of Stancu variant generalized (lambda, mu)-Bernstein operators. Various moment estimates are analyzed, and several aspects of local dir...
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The primary objective of this work is to explore various approximation properties of Stancu variant generalized (lambda, mu)-Bernstein operators. Various moment estimates are analyzed, and several aspects of local direct approximation theorems are investigated. Additionally, further approximation features of newly defined operators are delved into, such as the Voronovskaya-type asymptotic theorem and pointwise estimates. By comparing the proposed operator graphically and numerically with some linear positive operators known in the literature, it is evident that much better approximation results are achieved in terms of convergence behavior, calculation efficiency, and consistency. Finally, the newly defined operators are used to obtain a numerical solution for a special case of the fractional Volterra integral equation of the second kind.
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