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New advanced driver assistance system/automated driving (ADAS/AD) functions have the potential to significantly enhance the safety of vehicle passengers and road users, while also enabling new transportation applications and potentially reducing CO2 emissions. To achieve the next level of driving automation, i.e., SAE Level-3, physical test drives need to be supplemented by simulations in virtual test environments. A major challenge for today’s virtual test environments is to provide a realistic representation of the vehicle’s perception system (camera, lidar, radar). Therefore, new and improved sensor models are required to perform representative virtual tests that can supplement physical test drives. In this article, we present a computationally efficient, mathematically complete, and geometrically exact generic sensor modeling approach that solves the FOV (field of view) and occlusion task. We also discuss potential extensions, such as bounding-box cropping and sensor-specific, weather-dependent FOV-reduction approaches for camera, lidar, and radar. The performance of the new modeling approach is demonstrated using camera measurements from a test campaign conducted in Hungary in 2020 plus three artificial scenarios (a multi-target scenario with an adjacent truck occluding other road users and two traffic jam situations in which the ego vehicle is either a car or a truck). These scenarios are benchmarked against existing sensor modeling approaches that only exclude objects that are outside the sensor’s maximum detection range or angle. The modeling approach presented can be used as is or provide the basis for a more complex sensor model, as it reduces the number of potentially detectable targets and therefore improves the performance of subsequent simulation steps.

Understanding and perceiving three-dimensional scientific visualizations, such as volume rendering, benefit from visual cues produced by the shading models. The conventional approaches are local shading models since they are computationally inexpensive and straightforward to implement. However, the local shading models do not always provide proper visual cues since non-local information is not sufficiently taken into account for the shading. Global illumination models achieve better visual cues, but they are often computationally expensive. It has been shown that alternative illumination models, such as ambient occlusion, multidirectional shading, and shadows, provide decent perceptual cues. Although these models improve upon local shading models, they still require expensive preprocessing, extra GPU memory, and a high computational cost, which cause a lack of interactivity during the transfer function manipulations and light position changes. In this paper, we proposed an approximate image-space multidirectional occlusion shading model for the volume rendering. Our model was computationally less expensive compared to the global illumination models and did not require preprocessing. Moreover, interactive transfer function manipulations and light position changes were achievable. Our model simulated a wide range of shading behaviors, such as ambient occlusion and soft and hard shadows, and can be effortlessly applied to existing rendering systems such as direct volume rendering. We showed that the suggested model enhanced the visual cues with modest computational costs. [ABSTRACT FROM AUTHOR]

Understanding and perceiving three-dimensional scientific visualizations, such as volume rendering, benefit from visual cues produced by the shading models. The conventional approaches are local shading models since they are computationally inexpensive and straightforward to implement. However, the local shading models do not always provide proper visual cues since non-local information is not sufficiently taken into account for the shading. Global illumination models achieve better visual cues, but they are often computationally expensive. It has been shown that alternative illumination models, such as ambient occlusion, multidirectional shading, and shadows, provide decent perceptual cues. Although these models improve upon local shading models, they still require expensive preprocessing, extra GPU memory, and a high computational cost, which cause a lack of interactivity during the transfer function manipulations and light position changes. In this paper, we proposed an approximate image-space multidirectional occlusion shading model for the volume rendering. Our model was computationally less expensive compared to the global illumination models and did not require preprocessing. Moreover, interactive transfer function manipulations and light position changes were achievable. Our model simulated a wide range of shading behaviors, such as ambient occlusion and soft and hard shadows, and can be effortlessly applied to existing rendering systems such as direct volume rendering. We showed that the suggested model enhanced the visual cues with modest computational costs.

Occlusion is one of the most challenging problems in depth estimation. Previous work has modeled the single-occluder occlusion in light field and achieves good performances, however it is still difficult to obtain accurate depth for multioccluder occlusion. In this paper, we explore the complete occlusion model in light field and derive the occluder-consistency between the spatial and angular spaces, which is used as a guidance to select unoccluded views for each candidate occlusion point. Then, an antiocclusion energy function is built to regularize the depth map. Experimental results on both synthetic and real light-field datasets have demonstrated the advantages of the proposed algorithm compared with state-of-the-art algorithms of light-field depth estimation, especially in multioccluder cases. [ABSTRACT FROM PUBLISHER]

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Depth estimation for light field images is crucial in light field applications such as image-based rendering and refocusing. Previous learning-based methods com bining neural network with cost volume can achieve accurate depth estimation but fail in regions with occlusion. In this paper, a two-stage attention-based occlusion-aware light field depth estimation network is proposed. In the initial depth estimation stage, the sub-aperture images are divided into four groups based on different view directions and four initial cost volumes are constructed using the feature maps from each group to aggregate initial depth maps. Then in the refined depth estimation stage, the four aggregated volumes from the initial stage are fused into one based on the view attention, where features of views with less occlusion are highly weighted to provide more effective information. Experiment results demonstrate that the proposed method can accomplish robust and accurate depth estimation in the presence of occlusion, which ranks the first place on 4D light field benchmark in terms of most accuracy metrics. [ABSTRACT FROM AUTHOR]

Multi-object tracking has significant merit to our society. However, interactions among objects result in complex spatial occlusions, which gives rise to a challenging problem in tracking. We propose an adaptive weighing particle filter (AWPT) for tracking multiple objects and reasoning the occlusions among them. A weighing-occlusion modeling-weighing procedure is developed to adaptively weigh the particles. Moreover, we propose a stack occlusion model and define the operations on it to maintain the occlusion relationship. The experiments exhibit that the proposed method can effectively track fully occluded objects and reason about the occlusion relationships among them. [ABSTRACT FROM AUTHOR]

This study was designed to investigate whether magnesium sulphate prevents cerebral ischemic injury on an experimental rat model. Forty Sprague-Dawley rats were divided into 4 groups: I) the sham group; II) the group to which saline was applied prior to ischemia (control); III) the group that received MgSO4 (90 mg/ kg) intraperitoneally 30 minutes before ischemia; IV) the group that received MgSO4 (90 mg/ kg) intraperitoneally 30 minutes after ischemia. Infarct volumes were measured in all the rat groups by the use of MRI subsequently analyzed by the Workstation: Philips Easy Vision 5.2.1.1 Measurement analysis program. Total infarct volumes in the ischemic group that received saline without MgSO4, in the group that received MgSO4 after occlusion of the MCA and in the group that received MgSO4 before MCA occlusion were 231.7±34.03 mm³, 158.85±32.16 mm³ and 87.35±22.27 mm³ respectively. Total infarct volumes were significantly reduced in both the pre-occlusive and post-occlusive MgSO4 treatment groups (p<0.001). Our results support that magnesium displays a neuroprotective impact against cerebral ischemic injury. This therapeutic potential may have important clinical applicability if applied before neurovascular surgical interventions. However, the actual therapeutic potential of magnesium in humans and standardization of protocols need to be unveiled in further studies. [ABSTRACT FROM AUTHOR]

Purpose: To compare an endovascular technique with a well established surgical approach to achieve long-term occlusions of large porcine arteries while preserving the integrity of periarterial tissue.Methods: The femoral arteries in 11 pigs were occluded using surgical techniques on one side and blinded stent-grafts in the contralateral vessel. Feasibility, safety, primary and long-term success, and the extent of vascularization were determined over a 3-month period by conventional angiography and histological analysis. A subgroup of animals (n=5) was treated with a locally administered plasmid coding for vascular endothelial growth factor (pVEGF165) to compare both occlusion techniques under conditions of collateral growth induction.Results: The primary and long-term success rates for both occlusion models were 100%. Surgical occlusion of arteries resulted in a significant amount of scar dehiscence and local groin infection compared to the endograft-occluded side. There was no significant difference in capillary densities and collateralization of periarterial areas in a comparison of the occlusion technique: the cross-sectional area of the superficial femoral artery (SFA) was 300 +/- 24 mm2 for endovascular occlusion versus 320 +/- 23 mm2 for surgical occlusion (p=0.559). In the profunda femoris artery, respective values were 418 +/- 35 and 448 +/- 18 mm2 (p=0.474). The local delivery of pVEGF165 resulted in a significant increase in collateral growth in both occlusion models with comparable neovascularization: cross-sectional SFA area increased from 310 +/- 16 to 428 +/- 13 mm2 (p<0.0001); in the PFA, the area increased from 422 +/- 19 to 658 +/- 49 mm2 (p<0.0001).Conclusions: Endovascular arterial occlusions using blinded stent-grafts allow easy and safe creation of long-term occlusions. Previously described collateralization following surgical occlusions was not observed, indicating that those collaterals may be associated with wound healing rather than ischemia. The occlusion of arteries using blinded stent-grafts in pigs may therefore be an appropriate model for assessing the effects of angiogenic factors in vivo. [ABSTRACT FROM AUTHOR]

Copyright of Der Gynäkologe is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)