Objective image quality assessment(IQA)plays an important role in various visual communication systems,which can automatically and efficiently predict the perceived quality of images.The human eye is the ultimate eval...Objective image quality assessment(IQA)plays an important role in various visual communication systems,which can automatically and efficiently predict the perceived quality of images.The human eye is the ultimate evaluator for visual experience,thus the modeling of human visual system(HVS)is a core issue for objective IQA and visual experience optimization.The traditional model based on black box fitting has low interpretability and it is difficult to guide the experience optimization effectively,while the model based on physiological simulation is hard to integrate into practical visual communication services due to its high computational complexity.For bridging the gap between signal distortion and visual experience,in this paper,we propose a novel perceptual no-reference(NR)IQA algorithm based on structural computational modeling of HVS.According to the mechanism of the human brain,we divide the visual signal processing into a low-level visual layer,a middle-level visual layer and a high-level visual layer,which conduct pixel information processing,primitive information processing and global image information processing,respectively.The natural scene statistics(NSS)based features,deep features and free-energy based features are extracted from these three layers.The support vector regression(SVR)is employed to aggregate features to the final quality prediction.Extensive experimental comparisons on three widely used benchmark IQA databases(LIVE,CSIQ and TID2013)demonstrate that our proposed metric is highly competitive with or outperforms the state-of-the-art NR IQA measures.展开更多
To overcome the shortcomings of the Lee image enhancement algorithm and its improvement based on the logarithmic image processing(LIP) model, this paper proposes what we believe to be an effective image enhancement al...To overcome the shortcomings of the Lee image enhancement algorithm and its improvement based on the logarithmic image processing(LIP) model, this paper proposes what we believe to be an effective image enhancement algorithm. This algorithm introduces fuzzy entropy, makes full use of neighborhood information, fuzzy information and human visual characteristics.To enhance an image, this paper first carries out the reasonable fuzzy-3 partition of its histogram into the dark region, intermediate region and bright region. It then extracts the statistical characteristics of the three regions and adaptively selects the parameter αaccording to the statistical characteristics of the image’s gray-scale values. It also adds a useful nonlinear transform, thus increasing the ubiquity of the algorithm. Finally, the causes for the gray-scale value overcorrection that occurs in the traditional image enhancement algorithms are analyzed and their solutions are proposed.The simulation results show that our image enhancement algorithm can effectively suppress the noise of an image, enhance its contrast and visual effect, sharpen its edge and adjust its dynamic range.展开更多
A Robust Adaptive Video Encoder (RAVE) based on human visual model is proposed. The encoder combines the best features of Fine Granularity Scalable (FGS) coding, framedropping coding, video redundancy coding, and huma...A Robust Adaptive Video Encoder (RAVE) based on human visual model is proposed. The encoder combines the best features of Fine Granularity Scalable (FGS) coding, framedropping coding, video redundancy coding, and human visual model. According to packet loss and available bandwidth of the network, the encoder adjust the output bit rate by jointly adapting quantization step-size instructed by human visual model, rate shaping, and periodically inserting key frame. The proposed encoder is implemented based on MPEG-4 encoder and is compared with the case of a conventional FGS algorithm. It is shown that RAVE is a very efficient robust video encoder that provides improved visual quality for the receiver and consumes equal or less network resource. Results are confirmed by subjective tests and simulation tests.展开更多
Visual odometry is critical in visual simultaneous localization and mapping for robot navigation.However,the pose estimation performance of most current visual odometry algorithms degrades in scenes with unevenly dist...Visual odometry is critical in visual simultaneous localization and mapping for robot navigation.However,the pose estimation performance of most current visual odometry algorithms degrades in scenes with unevenly distributed features because dense features occupy excessive weight.Herein,a new human visual attention mechanism for point-and-line stereo visual odometry,which is called point-line-weight-mechanism visual odometry(PLWM-VO),is proposed to describe scene features in a global and balanced manner.A weight-adaptive model based on region partition and region growth is generated for the human visual attention mechanism,where sufficient attention is assigned to position-distinctive objects(sparse features in the environment).Furthermore,the sum of absolute differences algorithm is used to improve the accuracy of initialization for line features.Compared with the state-of-the-art method(ORB-VO),PLWM-VO show a 36.79%reduction in the absolute trajectory error on the Kitti and Euroc datasets.Although the time consumption of PLWM-VO is higher than that of ORB-VO,online test results indicate that PLWM-VO satisfies the real-time demand.The proposed algorithm not only significantly promotes the environmental adaptability of visual odometry,but also quantitatively demonstrates the superiority of the human visual attention mechanism.展开更多
The key to the wavelet based denoising teehniquea is how to manipulate the wavelet coefficients. By referring to the idea of Inclusive-OR in the design of circuits, this paper proposes a new algorithm called wavelet d...The key to the wavelet based denoising teehniquea is how to manipulate the wavelet coefficients. By referring to the idea of Inclusive-OR in the design of circuits, this paper proposes a new algorithm called wavelet domain Inclusive-OR denoising algorithm（WDIDA）, which distinguishes the wavelet coefficients belonging to image or noise by considering their phases and modulus maxima simultaneously. Using this new algorithm, the denoising effects are improved and the computation time is reduced. Furthermore, in order to enhance the edges of the image but not magnify noise, a contrast nonlinear enhancing algorithm is presented according to human visual properties. Compared with traditional enhancing algorithms, the algorithm that we proposed has a better noise reducing performanee , preserving edges and improving the visual quality of images.展开更多
针对现有全景图像质量评价模型观察空间和表示空间一致性缺失、局部质量融合能力受限等问题,提出基于局部特征非均匀提取的全景图像质量评价算法。该算法充分考虑人类视觉系统及全景图像投影特性,在特征域而非图像域设计细粒度、非均匀...针对现有全景图像质量评价模型观察空间和表示空间一致性缺失、局部质量融合能力受限等问题,提出基于局部特征非均匀提取的全景图像质量评价算法。该算法充分考虑人类视觉系统及全景图像投影特性,在特征域而非图像域设计细粒度、非均匀的局部特征提取策略;同时基于自注意力机制,在全局视角下统筹考虑整体感知质量对不同局部区域的依赖程度,有效聚合了各区域的局部感知特征。在全景图像数据集CVIQ、LIVE 3D VR和MAVQD上的实验结果表明,该算法性能优于现有全景图像质量评价算法,且所采用的不同模块均具有有效性。展开更多
可逆信息隐藏(reversible data hiding,RDH)失真包括像素失真和结构失真。考虑到人类视觉系统(human visual system,HVS)对图像结构失真的高敏感性,本文提出使用结构相似性指数(structural similarity index measure,SSIM)作为RDH的评...可逆信息隐藏(reversible data hiding,RDH)失真包括像素失真和结构失真。考虑到人类视觉系统(human visual system,HVS)对图像结构失真的高敏感性,本文提出使用结构相似性指数(structural similarity index measure,SSIM)作为RDH的评价指标。首先,通过分析峰值信噪比(peak signal-to-noise ratio,PSNR)与SSIM的理论增益关系,实现对两个指标的动态同步评估。随后,提出一种基于纹理区域优先选择的高SSIM的RDH方法。将载体图像划分为4个独立像素集进行图像预处理,精准找到纹理区域,进而按照背景复杂度由高到低的顺序嵌入信息。实验结果表明,优先在纹理区域中嵌入信息的策略减小了图像结构失真。在相同的嵌入率下,SSIM值及图像视觉质量均得到了提高。展开更多
In order to further improve the efficiency of video compression, we introduce a perceptual characteristics of Human Visual System (HVS) to video coding, and propose a novel video coding rate control algorithm based on...In order to further improve the efficiency of video compression, we introduce a perceptual characteristics of Human Visual System (HVS) to video coding, and propose a novel video coding rate control algorithm based on human visual saliency model in H.264/AVC. Firstly, we modifie Itti's saliency model. Secondly, target bits of each frame are allocated through the correlation of saliency region between the current and previous frame, and the complexity of each MB is modified through the saliency value and its Mean Absolute Difference (MAD) value. Lastly, the algorithm was implemented in JVT JM12.2. Simulation results show that, comparing with traditional rate control algorithm, the proposed one can reduce the coding bit rate and improve the reconstructed video subjective quality, especially for visual saliency region. It is very suitable for wireless video transmission.展开更多
While quality assessment is essential for testing, optimizing, benchmarking, monitoring, and inspecting related systems and services, it also plays an essential role in the design of virtually all visual signal proces...While quality assessment is essential for testing, optimizing, benchmarking, monitoring, and inspecting related systems and services, it also plays an essential role in the design of virtually all visual signal processing and communication algorithms, as well as various related decision-making processes. In this paper, we first provide an overview of recently derived quality assessment approaches for traditional visual signals (i.e., 2D images/videos), with highlights for new trends (such as machine learning approaches). On the other hand, with the ongoing development of devices and multimedia services, newly emerged visual signals (e.g., mobile/3D videos) are becoming more and more popular. This work focuses on recent progresses of quality metrics, which have been reviewed for the newly emerged forms of visual signals, which include scalable and mobile videos, High Dynamic Range (HDR) images, image segmentation results, 3D images/videos, and retargeted images.展开更多
Vision-simulated imagery―the process of generating images that mimic the human visual system―is a valuable tool with a wide spectrum of possible applications, including visual acuity measurements, personalized plann...Vision-simulated imagery―the process of generating images that mimic the human visual system―is a valuable tool with a wide spectrum of possible applications, including visual acuity measurements, personalized planning of corrective lenses and surgeries, vision-correcting displays, vision-related hardware development, and extended reality discomfort reduction. A critical property of human vision is that it is imperfect because of the highly influential wavefront aberrations that vary from person to person. This study provides an overview of the existing computational image generation techniques that properly simulate human vision in the presence of wavefront aberrations. These algorithms typically apply ray tracing with a detailed description of the simulated eye or utilize the point-spread func-tion of the eye to perform convolution on the input image. Based on the description of the vision simulation tech-niques, several of their characteristic features have been evaluated and some potential application areas and research directions have been outlined.展开更多
为提高煤矿井下无轨辅助运输胶轮车的运行安全性与智能化控制水平,针对传统监控方式与仿真建模技术难以直观展现运行状态和构建高保真模型的问题,提出了一种融合了新一代信息技术与数字孪生理念的无轨胶轮车运动仿真与人机交互系统。以...为提高煤矿井下无轨辅助运输胶轮车的运行安全性与智能化控制水平,针对传统监控方式与仿真建模技术难以直观展现运行状态和构建高保真模型的问题,提出了一种融合了新一代信息技术与数字孪生理念的无轨胶轮车运动仿真与人机交互系统。以具备多传感器设计的无轨胶轮车为研究对象,采用MATLAB/Simulink设计了系统架构与功能模块,结合CAN总线完成了多元传感器数据的标准化转换与高速传输。通过整车控制器(Vehicle Control Unit,VCU)的I/O接口实现了数字孪生模型与物理实体的实时数据交互,构建了虚实融合的运行环境,并实现了对车辆转矩、转速、制动压力等关键安全参数的连续监测。系统引入了基于物理建模与实时数据驱动的预测性仿真方法,能够高精度模拟车辆在不同工况下的动态响应,特别适用于VCU的程序优化与控制算法的参数调整。以某煤矿井下低速四轮转向工况为例,基于数字孪生模型构建的仿真平台复现了真实转弯环境,结合车辆动力学特性开展了多轮仿真试验,优化了比例-积分-微分(Proportional-Integral-Derivative,PID)控制参数。优化后的控制策略显著提升了车辆横摆角速度,减小了转弯半径,仿真结果与实测数据变化趋势高度一致:最大相对误差为1.34%,平均误差为0.85%,验证了模型的准确性与可靠性;控制系统整体时间延迟控制在30 ms以内,充分体现了系统的实时性。展开更多
Recent studies on no-reference image quality assessment (NR-IQA) methods usually learn to evaluate the image quality by regressing from human subjective scores of the training samples. This study presented an NR-IQA m...Recent studies on no-reference image quality assessment (NR-IQA) methods usually learn to evaluate the image quality by regressing from human subjective scores of the training samples. This study presented an NR-IQA method based on the basic image visual parameters without using human scored image databases in learning. We demonstrated that these features comprised the most basic characteristics for constructing an image and influencing the visual quality of an image. In this paper, the definitions, computational method, and relationships among these visual metrics were described. We subsequently proposed a no-reference assessment function, which was referred to as a visual parameter measurement index (VPMI), based on the integration of these visual metrics to assess image quality. It is established that the maximum of VPMI corresponds to the best quality of the color image. We verified this method using the popular assessment database—image quality assessment database (LIVE), and the results indicated that the proposed method matched better with the subjective assessment of human vision. Compared with other image quality assessment models, it is highly competitive. VPMI has low computational complexity, which makes it promising to implement in real-time image assessment systems.展开更多
Bicycle sharing system has emerged as a new mode of transportation in many big cities over the past decade.Since the large number of bicycle stations distribute widely in the city,it is difficult to identify their uni...Bicycle sharing system has emerged as a new mode of transportation in many big cities over the past decade.Since the large number of bicycle stations distribute widely in the city,it is difficult to identify their unique attributes and characteristics directly.Oriented to the real bicycle hire dataset in Hangzhou,China,the clustering analysis for the bicycle stations based on the temporal flow data was carried out firstly.Then,based on the spatial distribution and temporal attributes of calculated clusters,visual diagram and map were used to vividly analyze the bicycle hire behavior related to station category and study the travel rules of citizens.The experimental results demonstrate the relation between human mobility,the time of day,day of week and the station location.展开更多
Although ray tracing produces high-fidelity, realistic images, it is considered computationally burdensome when implemented on a high rendering rate system. Perception-driven rendering techniques generate images with ...Although ray tracing produces high-fidelity, realistic images, it is considered computationally burdensome when implemented on a high rendering rate system. Perception-driven rendering techniques generate images with minimal noise and distortion that are generally acceptable to the human visual system, thereby reducing rendering costs. In this paper, we introduce a perception-entropy-driven temporal reusing method to accelerate real-time ray tracing. We first build a just noticeable difference(JND) model to represent the uncertainty of ray samples and image space masking effects. Then, we expand the shading gradient through gradient max-pooling and gradient filtering to enlarge the visual receipt field. Finally, we dynamically optimize reusable time segments to improve the accuracy of temporal reusing. Compared with Monte Carlo ray tracing, our algorithm enhances frames per second(fps) by 1.93× to 2.96× at 8 to 16 samples per pixel, significantly accelerating the Monte Carlo ray tracing process while maintaining visual quality.展开更多
为解决现有VSLAM特征提取器在室内环境中对纹理和光照变化敏感、特征点冗余导致的局部依赖性过强以及硬件资源受限时的存储开销问题,提出了一种面向纹理的均匀FAST特征提取器(texture-oriented and homogenized FAST feature extractor,...为解决现有VSLAM特征提取器在室内环境中对纹理和光照变化敏感、特征点冗余导致的局部依赖性过强以及硬件资源受限时的存储开销问题,提出了一种面向纹理的均匀FAST特征提取器(texture-oriented and homogenized FAST feature extractor, TOHF)。结合HVS(human visual system),采用二阶段阈值策略来更敏感地应对纹理的清晰度和复杂度差异。根据特征点密度的变化来动态调整特征点的分布,在兼顾计算效率和存储开销的同时,保证特征点分布结构信息。在资源受限设备录制的数据集和官方Eu Roc数据集上基于ORB-SLAM3框架开展实验,采用匹配率、重投影误差、绝对轨迹误差(ATE)和耗时作为评估指标。实验结果表明:TOHF在视觉加惯导模式下带来更高精度和鲁棒性的同时,仍满足实时性要求。展开更多
基金This work was supported by National Natural Science Foundation of China(Nos.61831015 and 61901260)Key Research and Development Program of China(No.2019YFB1405902).
文摘Objective image quality assessment(IQA)plays an important role in various visual communication systems,which can automatically and efficiently predict the perceived quality of images.The human eye is the ultimate evaluator for visual experience,thus the modeling of human visual system(HVS)is a core issue for objective IQA and visual experience optimization.The traditional model based on black box fitting has low interpretability and it is difficult to guide the experience optimization effectively,while the model based on physiological simulation is hard to integrate into practical visual communication services due to its high computational complexity.For bridging the gap between signal distortion and visual experience,in this paper,we propose a novel perceptual no-reference(NR)IQA algorithm based on structural computational modeling of HVS.According to the mechanism of the human brain,we divide the visual signal processing into a low-level visual layer,a middle-level visual layer and a high-level visual layer,which conduct pixel information processing,primitive information processing and global image information processing,respectively.The natural scene statistics(NSS)based features,deep features and free-energy based features are extracted from these three layers.The support vector regression(SVR)is employed to aggregate features to the final quality prediction.Extensive experimental comparisons on three widely used benchmark IQA databases(LIVE,CSIQ and TID2013)demonstrate that our proposed metric is highly competitive with or outperforms the state-of-the-art NR IQA measures.
基金supported by the National Natural Science Foundation of China(61472324)
文摘To overcome the shortcomings of the Lee image enhancement algorithm and its improvement based on the logarithmic image processing(LIP) model, this paper proposes what we believe to be an effective image enhancement algorithm. This algorithm introduces fuzzy entropy, makes full use of neighborhood information, fuzzy information and human visual characteristics.To enhance an image, this paper first carries out the reasonable fuzzy-3 partition of its histogram into the dark region, intermediate region and bright region. It then extracts the statistical characteristics of the three regions and adaptively selects the parameter αaccording to the statistical characteristics of the image’s gray-scale values. It also adds a useful nonlinear transform, thus increasing the ubiquity of the algorithm. Finally, the causes for the gray-scale value overcorrection that occurs in the traditional image enhancement algorithms are analyzed and their solutions are proposed.The simulation results show that our image enhancement algorithm can effectively suppress the noise of an image, enhance its contrast and visual effect, sharpen its edge and adjust its dynamic range.
基金Supported by Innovation Fund of China(00C26224210641)
文摘A Robust Adaptive Video Encoder (RAVE) based on human visual model is proposed. The encoder combines the best features of Fine Granularity Scalable (FGS) coding, framedropping coding, video redundancy coding, and human visual model. According to packet loss and available bandwidth of the network, the encoder adjust the output bit rate by jointly adapting quantization step-size instructed by human visual model, rate shaping, and periodically inserting key frame. The proposed encoder is implemented based on MPEG-4 encoder and is compared with the case of a conventional FGS algorithm. It is shown that RAVE is a very efficient robust video encoder that provides improved visual quality for the receiver and consumes equal or less network resource. Results are confirmed by subjective tests and simulation tests.
基金Supported by Tianjin Municipal Natural Science Foundation of China(Grant No.19JCJQJC61600)Hebei Provincial Natural Science Foundation of China(Grant Nos.F2020202051,F2020202053).
文摘Visual odometry is critical in visual simultaneous localization and mapping for robot navigation.However,the pose estimation performance of most current visual odometry algorithms degrades in scenes with unevenly distributed features because dense features occupy excessive weight.Herein,a new human visual attention mechanism for point-and-line stereo visual odometry,which is called point-line-weight-mechanism visual odometry(PLWM-VO),is proposed to describe scene features in a global and balanced manner.A weight-adaptive model based on region partition and region growth is generated for the human visual attention mechanism,where sufficient attention is assigned to position-distinctive objects(sparse features in the environment).Furthermore,the sum of absolute differences algorithm is used to improve the accuracy of initialization for line features.Compared with the state-of-the-art method(ORB-VO),PLWM-VO show a 36.79%reduction in the absolute trajectory error on the Kitti and Euroc datasets.Although the time consumption of PLWM-VO is higher than that of ORB-VO,online test results indicate that PLWM-VO satisfies the real-time demand.The proposed algorithm not only significantly promotes the environmental adaptability of visual odometry,but also quantitatively demonstrates the superiority of the human visual attention mechanism.
文摘The key to the wavelet based denoising teehniquea is how to manipulate the wavelet coefficients. By referring to the idea of Inclusive-OR in the design of circuits, this paper proposes a new algorithm called wavelet domain Inclusive-OR denoising algorithm（WDIDA）, which distinguishes the wavelet coefficients belonging to image or noise by considering their phases and modulus maxima simultaneously. Using this new algorithm, the denoising effects are improved and the computation time is reduced. Furthermore, in order to enhance the edges of the image but not magnify noise, a contrast nonlinear enhancing algorithm is presented according to human visual properties. Compared with traditional enhancing algorithms, the algorithm that we proposed has a better noise reducing performanee , preserving edges and improving the visual quality of images.
文摘针对现有全景图像质量评价模型观察空间和表示空间一致性缺失、局部质量融合能力受限等问题,提出基于局部特征非均匀提取的全景图像质量评价算法。该算法充分考虑人类视觉系统及全景图像投影特性,在特征域而非图像域设计细粒度、非均匀的局部特征提取策略;同时基于自注意力机制,在全局视角下统筹考虑整体感知质量对不同局部区域的依赖程度,有效聚合了各区域的局部感知特征。在全景图像数据集CVIQ、LIVE 3D VR和MAVQD上的实验结果表明,该算法性能优于现有全景图像质量评价算法,且所采用的不同模块均具有有效性。
文摘可逆信息隐藏(reversible data hiding,RDH)失真包括像素失真和结构失真。考虑到人类视觉系统(human visual system,HVS)对图像结构失真的高敏感性,本文提出使用结构相似性指数(structural similarity index measure,SSIM)作为RDH的评价指标。首先,通过分析峰值信噪比(peak signal-to-noise ratio,PSNR)与SSIM的理论增益关系,实现对两个指标的动态同步评估。随后,提出一种基于纹理区域优先选择的高SSIM的RDH方法。将载体图像划分为4个独立像素集进行图像预处理,精准找到纹理区域,进而按照背景复杂度由高到低的顺序嵌入信息。实验结果表明,优先在纹理区域中嵌入信息的策略减小了图像结构失真。在相同的嵌入率下,SSIM值及图像视觉质量均得到了提高。
基金supported by National Natural Science Foundation of China under Grant No.610700800973 Sub-Program Projects under Grant No.2009CB320906+3 种基金National Science and Technology of Major Special Projects under Grant No.2010ZX03004-003S&T Planning Project of Hubei Provincial Department of Education under Grant No. Q20112805H&SPlanning Project of Hubei Provincial Department of Education under Grant No.2011jyte142Science Foundation of HubeiProvincial under Grant No.2010CDB05103
文摘In order to further improve the efficiency of video compression, we introduce a perceptual characteristics of Human Visual System (HVS) to video coding, and propose a novel video coding rate control algorithm based on human visual saliency model in H.264/AVC. Firstly, we modifie Itti's saliency model. Secondly, target bits of each frame are allocated through the correlation of saliency region between the current and previous frame, and the complexity of each MB is modified through the saliency value and its Mean Absolute Difference (MAD) value. Lastly, the algorithm was implemented in JVT JM12.2. Simulation results show that, comparing with traditional rate control algorithm, the proposed one can reduce the coding bit rate and improve the reconstructed video subjective quality, especially for visual saliency region. It is very suitable for wireless video transmission.
基金partially supported by the Research Grants Council of the Hong Kong SAR, China (Project CUHK 415712)the Ministry of Education Academic Research Fund (AcRF) Tier 2 in Singapore under Grant No. T208B1218
文摘While quality assessment is essential for testing, optimizing, benchmarking, monitoring, and inspecting related systems and services, it also plays an essential role in the design of virtually all visual signal processing and communication algorithms, as well as various related decision-making processes. In this paper, we first provide an overview of recently derived quality assessment approaches for traditional visual signals (i.e., 2D images/videos), with highlights for new trends (such as machine learning approaches). On the other hand, with the ongoing development of devices and multimedia services, newly emerged visual signals (e.g., mobile/3D videos) are becoming more and more popular. This work focuses on recent progresses of quality metrics, which have been reviewed for the newly emerged forms of visual signals, which include scalable and mobile videos, High Dynamic Range (HDR) images, image segmentation results, 3D images/videos, and retargeted images.
文摘Vision-simulated imagery―the process of generating images that mimic the human visual system―is a valuable tool with a wide spectrum of possible applications, including visual acuity measurements, personalized planning of corrective lenses and surgeries, vision-correcting displays, vision-related hardware development, and extended reality discomfort reduction. A critical property of human vision is that it is imperfect because of the highly influential wavefront aberrations that vary from person to person. This study provides an overview of the existing computational image generation techniques that properly simulate human vision in the presence of wavefront aberrations. These algorithms typically apply ray tracing with a detailed description of the simulated eye or utilize the point-spread func-tion of the eye to perform convolution on the input image. Based on the description of the vision simulation tech-niques, several of their characteristic features have been evaluated and some potential application areas and research directions have been outlined.
文摘为提高煤矿井下无轨辅助运输胶轮车的运行安全性与智能化控制水平,针对传统监控方式与仿真建模技术难以直观展现运行状态和构建高保真模型的问题,提出了一种融合了新一代信息技术与数字孪生理念的无轨胶轮车运动仿真与人机交互系统。以具备多传感器设计的无轨胶轮车为研究对象,采用MATLAB/Simulink设计了系统架构与功能模块,结合CAN总线完成了多元传感器数据的标准化转换与高速传输。通过整车控制器(Vehicle Control Unit,VCU)的I/O接口实现了数字孪生模型与物理实体的实时数据交互,构建了虚实融合的运行环境,并实现了对车辆转矩、转速、制动压力等关键安全参数的连续监测。系统引入了基于物理建模与实时数据驱动的预测性仿真方法,能够高精度模拟车辆在不同工况下的动态响应,特别适用于VCU的程序优化与控制算法的参数调整。以某煤矿井下低速四轮转向工况为例,基于数字孪生模型构建的仿真平台复现了真实转弯环境,结合车辆动力学特性开展了多轮仿真试验,优化了比例-积分-微分(Proportional-Integral-Derivative,PID)控制参数。优化后的控制策略显著提升了车辆横摆角速度,减小了转弯半径,仿真结果与实测数据变化趋势高度一致:最大相对误差为1.34%,平均误差为0.85%,验证了模型的准确性与可靠性;控制系统整体时间延迟控制在30 ms以内,充分体现了系统的实时性。
基金supported by the National Natural Science Foundation of China under Grants No.61773094,No.61573080,No.91420105,and No.61375115National Program on Key Basic Research Project(973 Program)under Grant No.2013CB329401+1 种基金National High-Tech R&D Program of China(863 Program)under Grant No.2015AA020505Sichuan Province Science and Technology Project under Grants No.2015SZ0141 and No.2018ZA0138
文摘Recent studies on no-reference image quality assessment (NR-IQA) methods usually learn to evaluate the image quality by regressing from human subjective scores of the training samples. This study presented an NR-IQA method based on the basic image visual parameters without using human scored image databases in learning. We demonstrated that these features comprised the most basic characteristics for constructing an image and influencing the visual quality of an image. In this paper, the definitions, computational method, and relationships among these visual metrics were described. We subsequently proposed a no-reference assessment function, which was referred to as a visual parameter measurement index (VPMI), based on the integration of these visual metrics to assess image quality. It is established that the maximum of VPMI corresponds to the best quality of the color image. We verified this method using the popular assessment database—image quality assessment database (LIVE), and the results indicated that the proposed method matched better with the subjective assessment of human vision. Compared with other image quality assessment models, it is highly competitive. VPMI has low computational complexity, which makes it promising to implement in real-time image assessment systems.
基金the Public Projects of Zhejiang Province,China(Nos.2016C33110,2015C33067)National Natural Science Foundations of China(Nos.61602141,61473108,61402141)
文摘Bicycle sharing system has emerged as a new mode of transportation in many big cities over the past decade.Since the large number of bicycle stations distribute widely in the city,it is difficult to identify their unique attributes and characteristics directly.Oriented to the real bicycle hire dataset in Hangzhou,China,the clustering analysis for the bicycle stations based on the temporal flow data was carried out firstly.Then,based on the spatial distribution and temporal attributes of calculated clusters,visual diagram and map were used to vividly analyze the bicycle hire behavior related to station category and study the travel rules of citizens.The experimental results demonstrate the relation between human mobility,the time of day,day of week and the station location.
基金supported by the National Natural Science Foundation of China (No.U19A2063)the Jilin Provincial Science&Technology Development Program of China (No.20230201080GX)。
文摘Although ray tracing produces high-fidelity, realistic images, it is considered computationally burdensome when implemented on a high rendering rate system. Perception-driven rendering techniques generate images with minimal noise and distortion that are generally acceptable to the human visual system, thereby reducing rendering costs. In this paper, we introduce a perception-entropy-driven temporal reusing method to accelerate real-time ray tracing. We first build a just noticeable difference(JND) model to represent the uncertainty of ray samples and image space masking effects. Then, we expand the shading gradient through gradient max-pooling and gradient filtering to enlarge the visual receipt field. Finally, we dynamically optimize reusable time segments to improve the accuracy of temporal reusing. Compared with Monte Carlo ray tracing, our algorithm enhances frames per second(fps) by 1.93× to 2.96× at 8 to 16 samples per pixel, significantly accelerating the Monte Carlo ray tracing process while maintaining visual quality.
文摘为解决现有VSLAM特征提取器在室内环境中对纹理和光照变化敏感、特征点冗余导致的局部依赖性过强以及硬件资源受限时的存储开销问题,提出了一种面向纹理的均匀FAST特征提取器(texture-oriented and homogenized FAST feature extractor, TOHF)。结合HVS(human visual system),采用二阶段阈值策略来更敏感地应对纹理的清晰度和复杂度差异。根据特征点密度的变化来动态调整特征点的分布,在兼顾计算效率和存储开销的同时,保证特征点分布结构信息。在资源受限设备录制的数据集和官方Eu Roc数据集上基于ORB-SLAM3框架开展实验,采用匹配率、重投影误差、绝对轨迹误差(ATE)和耗时作为评估指标。实验结果表明:TOHF在视觉加惯导模式下带来更高精度和鲁棒性的同时,仍满足实时性要求。
