Color inconsistency between views is an important problem to be solved in multi-view video systems. A multi-view video color correction method using dynamic programming is proposed. Three-dimensional histograms are co...Color inconsistency between views is an important problem to be solved in multi-view video systems. A multi-view video color correction method using dynamic programming is proposed. Three-dimensional histograms are constructed with sequential conditional probability in HSI color space. Then, dynamic programming is used to seek the best color mapping relation with the minimum cost path between target image histogram and source image histogram. Finally, video tracking technique is performed to correct multi-view video. Experimental results show that the proposed method can obtain better subjective and objective performance in color correction.展开更多
In the production of the sucker rod well, the dynamic liquid level is important for the production efficiency and safety in the lifting process. It is influenced by multi-source data which need to be combined for the ...In the production of the sucker rod well, the dynamic liquid level is important for the production efficiency and safety in the lifting process. It is influenced by multi-source data which need to be combined for the dynamic liquid level real-time calculation. In this paper, the multi-source data are regarded as the different views including the load of the sucker rod and liquid in the wellbore, the image of the dynamometer card and production dynamics parameters. These views can be fused by the multi-branch neural network with special fusion layer. With this method, the features of different views can be extracted by considering the difference of the modality and physical meaning between them. Then, the extraction results which are selected by multinomial sampling can be the input of the fusion layer.During the fusion process, the availability under different views determines whether the views are fused in the fusion layer or not. In this way, not only the correlation between the views can be considered, but also the missing data can be processed automatically. The results have shown that the load and production features fusion(the method proposed in this paper) performs best with the lowest mean absolute error(MAE) 39.63 m, followed by the features concatenation with MAE 42.47 m. They both performed better than only a single view and the lower MAE of the features fusion indicates that its generalization ability is stronger. In contrast, the image feature as a single view contributes little to the accuracy improvement after fused with other views with the highest MAE. When there is data missing in some view, compared with the features concatenation, the multi-view features fusion will not result in the unavailability of a large number of samples. When the missing rate is 10%, 30%, 50% and 80%, the method proposed in this paper can reduce MAE by 5.8, 7, 9.3 and 20.3 m respectively. In general, the multi-view features fusion method proposed in this paper can improve the accuracy obviously and process the missing data effectively, which helps provide technical support for real-time monitoring of the dynamic liquid level in oil fields.展开更多
This paper presents a free viewpoint video （FVV） system based on ray-space interpolation method The new algorithm matches individual pixels in corresponding scanline pairs by using a ruing technique. A sparse interm...This paper presents a free viewpoint video （FVV） system based on ray-space interpolation method The new algorithm matches individual pixels in corresponding scanline pairs by using a ruing technique. A sparse intermediate view disparity map is projected from matched dynamic programpixels firstly, and the holes （occluded pixels） are filled in by propagating the disparity of neighboring background pixels. After interpolating dense view images, an arbitrary virtual view image can be easily rendered from the dense ray-space converted from these view images. The proposed method is evaluated on the Middlebury data set and compared with other methods, experimental results show that the better quality of the intermediate view is obtained and the corresponding computational complexity is reduced significantly.展开更多
This study addresses the role of R&D leverage in SMEs’performance creation.The authors do so by considering SMEs’high resource dependence due to isomorphism.We propose that R&D leverage,with a presence of dy...This study addresses the role of R&D leverage in SMEs’performance creation.The authors do so by considering SMEs’high resource dependence due to isomorphism.We propose that R&D leverage,with a presence of dynamic capabilities,plays a moderating role in the relation between resource investments and performance.This study,which focused on Taiwan’s SMEs,conducts a questionnaire survey using the hierarchical sampling technique,across various industries and geographic areas in Taiwan.The empirical findings reveal that R&D leverage as an essential leveler in resource management enhances resource advantages.展开更多
森林火点检测在林火应急救援中起着至关重要的作用.鉴于现有模型在样本质量、多尺度检测以及多视角图像泛化能力方面存在不足,以YOLOv7为基础,提出一种森林火点目标检测方法FFD-YOLO(forest fire detection based on YOLO).首先,构建多...森林火点检测在林火应急救援中起着至关重要的作用.鉴于现有模型在样本质量、多尺度检测以及多视角图像泛化能力方面存在不足,以YOLOv7为基础,提出一种森林火点目标检测方法FFD-YOLO(forest fire detection based on YOLO).首先,构建多视角可见光图像森林火灾高点检测数据集FFHPV(forest fire of high point view),旨在增强模型对多视角火点知识的学习能力;其次,引入全维动态卷积,构建空间金字塔池化层(OD-SPP),以此提升模型针对多视角数据的火点特征提取能力;最后,引入具有动态非单调聚焦机制的边界框定位损失函数Wise-IoU(wise intersection over union),降低低质量数据对模型精度的影响,提高小目标火点的检测能力.实验结果表明:所提出的FFD-YOLO方法相较于YOLOv7,精度提高3.9%,召回率提高3.7%,均值平均精度提高4.0%,F1分数提高0.038;同时,在与YOLOv5、YOLOv8、DDQ(dense distinct query)、DINO(detection transformer with improved denoising anchor boxes)、Faster R-CNN、Sparse R-CNN、Mask R-CNN、FCOS和YOLOX的对比实验中,FFD-YOLO具有最高的精度75.3%、召回率73.8%、均值平均精度77.6%和F1分数0.745,验证了该方法的可行性与有效性.展开更多
Novel space-time view synthesis for monocular video is a highly challenging task:both static and dynamic objects usually appear in the video,but only a single view of the current scene is available,resulting in inaccu...Novel space-time view synthesis for monocular video is a highly challenging task:both static and dynamic objects usually appear in the video,but only a single view of the current scene is available,resulting in inaccurate synthesis results.To address this challenge,we propose FRNeRF,a novel spacetime view synthesis method with a fusion regularization field.Specifically,we design a 2D-3D fusion regularization field for the original dynamic neural field,which helps reduce blurring of dynamic objects in the scene.In addition,we add image prior features to the hierarchical sampling to solve the problem that the traditional hierarchical sampling strategy cannot obtain sufficient sampling points during training.We evaluate our method extensively on multiple datasets and show the results of dynamic space-time view synthesis.Our method achieves state-of-the-art performance both qualitatively and quantitatively.展开更多
A new method is proposed for synthesizing intermediate views from a pair of stereoscopic images. In order to synthesize high-quality intermediate views, the block matching method together with a simplified multi-windo...A new method is proposed for synthesizing intermediate views from a pair of stereoscopic images. In order to synthesize high-quality intermediate views, the block matching method together with a simplified multi-window technique and dynamic programming is used in the process of disparity estimation. Then occlusion detection is performed to locate occluded regions and their disparities are compensated. After the projecton of the left-to-right and right-to-left disparities onto the intermediate image, intermediate view is synthesized considering occluded regions. Experimental results show that our synthesis method can obtain intermediate views with higher quality.展开更多
基金supported by the National Natural Science Foundation of China (60672073)the Program for New Century Excellent Talents in University (NCET-06-0537)+1 种基金the Natural Science Foundation of Ningbo (2008A610016)the K.C.Wong Magna Fund in Ningbo University.
文摘Color inconsistency between views is an important problem to be solved in multi-view video systems. A multi-view video color correction method using dynamic programming is proposed. Three-dimensional histograms are constructed with sequential conditional probability in HSI color space. Then, dynamic programming is used to seek the best color mapping relation with the minimum cost path between target image histogram and source image histogram. Finally, video tracking technique is performed to correct multi-view video. Experimental results show that the proposed method can obtain better subjective and objective performance in color correction.
基金supported by the National Natural Science Foundation of China under Grant 52325402, 52274057, 52074340 and 51874335the National Key R&D Program of China under Grant 2023YFB4104200+1 种基金the Major Scientific and Technological Projects of CNOOC under Grant CCL2022RCPS0397RSN111 Project under Grant B08028。
文摘In the production of the sucker rod well, the dynamic liquid level is important for the production efficiency and safety in the lifting process. It is influenced by multi-source data which need to be combined for the dynamic liquid level real-time calculation. In this paper, the multi-source data are regarded as the different views including the load of the sucker rod and liquid in the wellbore, the image of the dynamometer card and production dynamics parameters. These views can be fused by the multi-branch neural network with special fusion layer. With this method, the features of different views can be extracted by considering the difference of the modality and physical meaning between them. Then, the extraction results which are selected by multinomial sampling can be the input of the fusion layer.During the fusion process, the availability under different views determines whether the views are fused in the fusion layer or not. In this way, not only the correlation between the views can be considered, but also the missing data can be processed automatically. The results have shown that the load and production features fusion(the method proposed in this paper) performs best with the lowest mean absolute error(MAE) 39.63 m, followed by the features concatenation with MAE 42.47 m. They both performed better than only a single view and the lower MAE of the features fusion indicates that its generalization ability is stronger. In contrast, the image feature as a single view contributes little to the accuracy improvement after fused with other views with the highest MAE. When there is data missing in some view, compared with the features concatenation, the multi-view features fusion will not result in the unavailability of a large number of samples. When the missing rate is 10%, 30%, 50% and 80%, the method proposed in this paper can reduce MAE by 5.8, 7, 9.3 and 20.3 m respectively. In general, the multi-view features fusion method proposed in this paper can improve the accuracy obviously and process the missing data effectively, which helps provide technical support for real-time monitoring of the dynamic liquid level in oil fields.
基金the Natural Science Foundation of China(No.60472100,60672073)the Program for New Century Excellent Talents in University(No.NCET-06-0537)the Key Project of Chinese Ministry of Education(No.206059)
文摘This paper presents a free viewpoint video （FVV） system based on ray-space interpolation method The new algorithm matches individual pixels in corresponding scanline pairs by using a ruing technique. A sparse intermediate view disparity map is projected from matched dynamic programpixels firstly, and the holes （occluded pixels） are filled in by propagating the disparity of neighboring background pixels. After interpolating dense view images, an arbitrary virtual view image can be easily rendered from the dense ray-space converted from these view images. The proposed method is evaluated on the Middlebury data set and compared with other methods, experimental results show that the better quality of the intermediate view is obtained and the corresponding computational complexity is reduced significantly.
文摘This study addresses the role of R&D leverage in SMEs’performance creation.The authors do so by considering SMEs’high resource dependence due to isomorphism.We propose that R&D leverage,with a presence of dynamic capabilities,plays a moderating role in the relation between resource investments and performance.This study,which focused on Taiwan’s SMEs,conducts a questionnaire survey using the hierarchical sampling technique,across various industries and geographic areas in Taiwan.The empirical findings reveal that R&D leverage as an essential leveler in resource management enhances resource advantages.
文摘森林火点检测在林火应急救援中起着至关重要的作用.鉴于现有模型在样本质量、多尺度检测以及多视角图像泛化能力方面存在不足,以YOLOv7为基础,提出一种森林火点目标检测方法FFD-YOLO(forest fire detection based on YOLO).首先,构建多视角可见光图像森林火灾高点检测数据集FFHPV(forest fire of high point view),旨在增强模型对多视角火点知识的学习能力;其次,引入全维动态卷积,构建空间金字塔池化层(OD-SPP),以此提升模型针对多视角数据的火点特征提取能力;最后,引入具有动态非单调聚焦机制的边界框定位损失函数Wise-IoU(wise intersection over union),降低低质量数据对模型精度的影响,提高小目标火点的检测能力.实验结果表明:所提出的FFD-YOLO方法相较于YOLOv7,精度提高3.9%,召回率提高3.7%,均值平均精度提高4.0%,F1分数提高0.038;同时,在与YOLOv5、YOLOv8、DDQ(dense distinct query)、DINO(detection transformer with improved denoising anchor boxes)、Faster R-CNN、Sparse R-CNN、Mask R-CNN、FCOS和YOLOX的对比实验中,FFD-YOLO具有最高的精度75.3%、召回率73.8%、均值平均精度77.6%和F1分数0.745,验证了该方法的可行性与有效性.
基金supported in part by National Key R&D Program of China(2023YFC3082100)National Natural Science Foundation of China(62122058 and 62171317)Science Fund for Distinguished Young Scholars of Tianjin(No.22JCJQJC00040).
文摘Novel space-time view synthesis for monocular video is a highly challenging task:both static and dynamic objects usually appear in the video,but only a single view of the current scene is available,resulting in inaccurate synthesis results.To address this challenge,we propose FRNeRF,a novel spacetime view synthesis method with a fusion regularization field.Specifically,we design a 2D-3D fusion regularization field for the original dynamic neural field,which helps reduce blurring of dynamic objects in the scene.In addition,we add image prior features to the hierarchical sampling to solve the problem that the traditional hierarchical sampling strategy cannot obtain sufficient sampling points during training.We evaluate our method extensively on multiple datasets and show the results of dynamic space-time view synthesis.Our method achieves state-of-the-art performance both qualitatively and quantitatively.
文摘A new method is proposed for synthesizing intermediate views from a pair of stereoscopic images. In order to synthesize high-quality intermediate views, the block matching method together with a simplified multi-window technique and dynamic programming is used in the process of disparity estimation. Then occlusion detection is performed to locate occluded regions and their disparities are compensated. After the projecton of the left-to-right and right-to-left disparities onto the intermediate image, intermediate view is synthesized considering occluded regions. Experimental results show that our synthesis method can obtain intermediate views with higher quality.
