Surveillance systems can take various forms,but gait-based surveillance is emerging as a powerful approach due to its ability to identify individuals without requiring their cooperation.In the existing studies,several...Surveillance systems can take various forms,but gait-based surveillance is emerging as a powerful approach due to its ability to identify individuals without requiring their cooperation.In the existing studies,several approaches have been suggested for gait recognition;nevertheless,the performance of existing systems is often degraded in real-world conditions due to covariate factors such as occlusions,clothing changes,walking speed,and varying camera viewpoints.Furthermore,most existing research focuses on single-person gait recognition;however,counting,tracking,detecting,and recognizing individuals in dual-subject settings with occlusions remains a challenging task.Therefore,this research proposed a variant of an automated gait model for occluded dual-subject walk scenarios.More precisely,in the proposed method,we have designed a deep learning(DL)-based dual-subject gait model(DSG)involving three modules.The first module handles silhouette segmentation,localization,and counting(SLC)using Mask-RCNN with MobileNetV2.The next stage uses a Convolutional block attention module(CBAM)-based Siamese network for frame-level tracking with a modified gallery setting.Following the last,gait recognition based on regionbased deep learning is proposed for dual-subject gait recognition.The proposed method,tested on Shri Mata Vaishno Devi University(SMVDU)-Multi-Gait and Single-Gait datasets,shows strong performance with 94.00%segmentation,58.36%tracking,and 63.04%gait recognition accuracy in dual-subject walk scenarios.展开更多
The motor and trailer cars of a high-speed train were modeled as a multi-rigid body system with two suspensions. According to structural characteristic of a slab track, a new spatial vibration model of track segment e...The motor and trailer cars of a high-speed train were modeled as a multi-rigid body system with two suspensions. According to structural characteristic of a slab track, a new spatial vibration model of track segment element of the slab track was put forward. The spatial vibration equation set of the high-speed train and slab track system was then established on the basis of the principle of total potential energy with stationary value in elastic system dynamics and the rule of ＂set-in-right-position＂ for formulating system matrices. The equation set was solved by the Wilson-θ direct integration method. The contents mentioned above constitute the analysis theory of spatial vibration of high-speed train and slab track system. The theory was then verified by the high-speed running experiment carried out on the slab track in the Qinghuangdao-Shenyang passenger transport line. The results show that the calculated results agree well with the measured rcsults, such as the calculated lateral and vertical rail displacements are 0.82 mm and 0.9 mm and the measured ones 0.75 mm and 0.93 mm, respectively; the calculated lateral and vertical wheel-rail forces are 8.9 kN and 102.3 kN and the measured ones 8.6 kN and 80.2 kN, respectively. The interpolation method, that is, the lateral finite strip and slab segment element, for slab deformation proposed is of simplification and applicability compared with the traditional plate element method. All of these demonstrate the reliability of the theory proposed.展开更多
A multifeature statistical image segmentation algorithm is described. Multiple features such as grey, edge magnitude and correlation are combined to form a multidimensional space statistics. The statistical algorithm ...A multifeature statistical image segmentation algorithm is described. Multiple features such as grey, edge magnitude and correlation are combined to form a multidimensional space statistics. The statistical algorithm is used to segment an image using the decision curved surface determined by the multidimensional feature function. The segmentation problem which is difficult to solve using the features independently will be readily solved using the same features jointly. An adaptive segmentation algorithm is discussed. Test results of the real-time TV tracker newly developed have shown that the segmentation algorithm discussed here improves effectively the image segmentation quality and system tracking performance.展开更多
Automated segmentation and tracking of cells in actively developing tissues can provide high-throughput and quantitative spatiotemporal measurements of a range of cell behaviors; cell expansion and cell-division kinet...Automated segmentation and tracking of cells in actively developing tissues can provide high-throughput and quantitative spatiotemporal measurements of a range of cell behaviors; cell expansion and cell-division kinetics leading to a better understanding of the underlying dynamics of morphogenesis. Here, we have studied the problem of constructing cell lineages in time-lapse volumetric image stacks obtained using Confocal Laser Scanning Microscopy （CLSM）. The novel contribution of the work lies in its ability to segment and track cells in densely packed tissue, the shoot apical meristem （SAM）, through the use of a close-loop, adaptive segmentation, and tracking approach. The tracking output acts as an indicator of the quality of segmentation and, in turn, the segmentation can be improved to obtain better tracking results. We construct an optimization function that minimizes the segmentation error, which is, in turn, estimated from the tracking results. This adaptive approach significantly improves both tracking and segmentation when compared to an open loop framework in which segmentation and tracking modules operate separately.展开更多
We describe the algorithm to reconstruct the charged tracks for BESⅢ main drift chamber at BEPCⅡ, including the track finding and fitting. With a new method of the Track Segment Finder （TSF）, the results of presen...We describe the algorithm to reconstruct the charged tracks for BESⅢ main drift chamber at BEPCⅡ, including the track finding and fitting. With a new method of the Track Segment Finder （TSF）, the results of present study indicate that the algorithm can reconstruct the charged tracks over a wide range of momentum with high efficiency, while improving the robustness against the background noise in the drift chamber. The overall performances, including spatial resolution, momentum resolution and secondary vertices reconstruction efficiency, etc. satisfy the requirements of BESⅢ experiment.展开更多
Detecting and tracking multiple targets simultaneously for space-based surveillance requires multiple cameras,which leads to a large system volume and weight. To address this problem, we propose a wide-field detection...Detecting and tracking multiple targets simultaneously for space-based surveillance requires multiple cameras,which leads to a large system volume and weight. To address this problem, we propose a wide-field detection and tracking system using the segmented planar imaging detector for electro-optical reconnaissance. This study realizes two operating modes by changing the working paired lenslets and corresponding waveguide arrays： a detection mode and a tracking mode. A model system was simulated and evaluated using the peak signal-to-noise ratio method. The simulation results indicate that the detection and tracking system can realize wide-field detection and narrow-field, multi-target, high-resolution tracking without moving parts.展开更多
The relative differences in coordinates of Cylindrical Gas Electron Multiplier Detector-based Inner Tracker（CGEM-IT） clusters are studied to search for track segments in CGEM-IT for the BESIII experiment.With the fu...The relative differences in coordinates of Cylindrical Gas Electron Multiplier Detector-based Inner Tracker（CGEM-IT） clusters are studied to search for track segments in CGEM-IT for the BESIII experiment.With the full simulation of single muon track samples, clear patterns are found and parameterized for the correct cluster combinations. The cluster combinations satisfying the patterns are selected as track segment candidates in CGEM-IT with an efficiency higher than 99%. The parameters of the track segments are obtained by a helix fitting.Some χ^2 quantities, evaluating the differences in track parameters between the track segments in CGEM-IT and the tracks found in the outer drift chamber, are calculated and used to match them. Proper χ^2 requirements are determined as a function of transverse momentum and the matching efficiency is found to be reasonable.展开更多
基金supported by the MSIT(Ministry of Science and ICT),Republic of Korea,under the Convergence Security Core Talent Training Business Support Program(IITP-2025-RS-2023-00266605)supervised by the IITP(Institute for Information&Communications Technology Planning&Evaluation).
文摘Surveillance systems can take various forms,but gait-based surveillance is emerging as a powerful approach due to its ability to identify individuals without requiring their cooperation.In the existing studies,several approaches have been suggested for gait recognition;nevertheless,the performance of existing systems is often degraded in real-world conditions due to covariate factors such as occlusions,clothing changes,walking speed,and varying camera viewpoints.Furthermore,most existing research focuses on single-person gait recognition;however,counting,tracking,detecting,and recognizing individuals in dual-subject settings with occlusions remains a challenging task.Therefore,this research proposed a variant of an automated gait model for occluded dual-subject walk scenarios.More precisely,in the proposed method,we have designed a deep learning(DL)-based dual-subject gait model(DSG)involving three modules.The first module handles silhouette segmentation,localization,and counting(SLC)using Mask-RCNN with MobileNetV2.The next stage uses a Convolutional block attention module(CBAM)-based Siamese network for frame-level tracking with a modified gallery setting.Following the last,gait recognition based on regionbased deep learning is proposed for dual-subject gait recognition.The proposed method,tested on Shri Mata Vaishno Devi University(SMVDU)-Multi-Gait and Single-Gait datasets,shows strong performance with 94.00%segmentation,58.36%tracking,and 63.04%gait recognition accuracy in dual-subject walk scenarios.
基金Project(2007CB714706) supported by the National Basic Research Program of ChinaProject (50678176) supported by the National Natural Science Foundation of ChinaProject(NCET-07-0866) supported by the Program for New Century Excellent Talents in University
文摘The motor and trailer cars of a high-speed train were modeled as a multi-rigid body system with two suspensions. According to structural characteristic of a slab track, a new spatial vibration model of track segment element of the slab track was put forward. The spatial vibration equation set of the high-speed train and slab track system was then established on the basis of the principle of total potential energy with stationary value in elastic system dynamics and the rule of ＂set-in-right-position＂ for formulating system matrices. The equation set was solved by the Wilson-θ direct integration method. The contents mentioned above constitute the analysis theory of spatial vibration of high-speed train and slab track system. The theory was then verified by the high-speed running experiment carried out on the slab track in the Qinghuangdao-Shenyang passenger transport line. The results show that the calculated results agree well with the measured rcsults, such as the calculated lateral and vertical rail displacements are 0.82 mm and 0.9 mm and the measured ones 0.75 mm and 0.93 mm, respectively; the calculated lateral and vertical wheel-rail forces are 8.9 kN and 102.3 kN and the measured ones 8.6 kN and 80.2 kN, respectively. The interpolation method, that is, the lateral finite strip and slab segment element, for slab deformation proposed is of simplification and applicability compared with the traditional plate element method. All of these demonstrate the reliability of the theory proposed.
文摘A multifeature statistical image segmentation algorithm is described. Multiple features such as grey, edge magnitude and correlation are combined to form a multidimensional space statistics. The statistical algorithm is used to segment an image using the decision curved surface determined by the multidimensional feature function. The segmentation problem which is difficult to solve using the features independently will be readily solved using the same features jointly. An adaptive segmentation algorithm is discussed. Test results of the real-time TV tracker newly developed have shown that the segmentation algorithm discussed here improves effectively the image segmentation quality and system tracking performance.
文摘Automated segmentation and tracking of cells in actively developing tissues can provide high-throughput and quantitative spatiotemporal measurements of a range of cell behaviors; cell expansion and cell-division kinetics leading to a better understanding of the underlying dynamics of morphogenesis. Here, we have studied the problem of constructing cell lineages in time-lapse volumetric image stacks obtained using Confocal Laser Scanning Microscopy （CLSM）. The novel contribution of the work lies in its ability to segment and track cells in densely packed tissue, the shoot apical meristem （SAM）, through the use of a close-loop, adaptive segmentation, and tracking approach. The tracking output acts as an indicator of the quality of segmentation and, in turn, the segmentation can be improved to obtain better tracking results. We construct an optimization function that minimizes the segmentation error, which is, in turn, estimated from the tracking results. This adaptive approach significantly improves both tracking and segmentation when compared to an open loop framework in which segmentation and tracking modules operate separately.
基金Supported by CAS Knowledge Innovation Project(U-602,U-34)National Natural Science Foundation of China(10491300,10491303,10605030)100 Talents Program of CAS(U-25,U-54)
文摘We describe the algorithm to reconstruct the charged tracks for BESⅢ main drift chamber at BEPCⅡ, including the track finding and fitting. With a new method of the Track Segment Finder （TSF）, the results of present study indicate that the algorithm can reconstruct the charged tracks over a wide range of momentum with high efficiency, while improving the robustness against the background noise in the drift chamber. The overall performances, including spatial resolution, momentum resolution and secondary vertices reconstruction efficiency, etc. satisfy the requirements of BESⅢ experiment.
基金supported by the Foundation of Youth Innovation Promotion Association,Chinese Academy of Sciences(No.20150192)
文摘Detecting and tracking multiple targets simultaneously for space-based surveillance requires multiple cameras,which leads to a large system volume and weight. To address this problem, we propose a wide-field detection and tracking system using the segmented planar imaging detector for electro-optical reconnaissance. This study realizes two operating modes by changing the working paired lenslets and corresponding waveguide arrays： a detection mode and a tracking mode. A model system was simulated and evaluated using the peak signal-to-noise ratio method. The simulation results indicate that the detection and tracking system can realize wide-field detection and narrow-field, multi-target, high-resolution tracking without moving parts.
基金Supported by National Key Basic Research Program of China(2015CB856706)National Natural Science Foundation of China(11575222,11205184,11205182,11121092,11475185)Joint Funds of National Natural Science Foundation of China(U1232201)
文摘The relative differences in coordinates of Cylindrical Gas Electron Multiplier Detector-based Inner Tracker（CGEM-IT） clusters are studied to search for track segments in CGEM-IT for the BESIII experiment.With the full simulation of single muon track samples, clear patterns are found and parameterized for the correct cluster combinations. The cluster combinations satisfying the patterns are selected as track segment candidates in CGEM-IT with an efficiency higher than 99%. The parameters of the track segments are obtained by a helix fitting.Some χ^2 quantities, evaluating the differences in track parameters between the track segments in CGEM-IT and the tracks found in the outer drift chamber, are calculated and used to match them. Proper χ^2 requirements are determined as a function of transverse momentum and the matching efficiency is found to be reasonable.
