Theγ-rays are widely and abundantly present in strong nuclear radiation environments,and when they act on the camera equipment used to obtain environmental visual information on nuclear robots,radiation effects will ...Theγ-rays are widely and abundantly present in strong nuclear radiation environments,and when they act on the camera equipment used to obtain environmental visual information on nuclear robots,radiation effects will occur,which will degrade the performance of the camera system,reduce the imaging quality,and even cause catastrophic consequences.Color reducibility is an important index for evaluating the imaging quality of color camera,but its degradation mechanism in a nuclear radiation environment is still unclear.In this paper,theγ-ray irradiation experiments of CMOS cameras were carried out to analyse the degradation law of the camera’s color reducibility with cumulative irradiation and reveal the degradation mechanism of the color information of the CMOS camera underγ-ray irradiation.The results show that the spectral response of CMOS image sensor(CIS)and the spectral transmittance of lens after irradiation affect the values of a^(*)and b^(*)in the LAB color model.While the full well capacity(FWC)of CIS and transmittance of lens affect the value of L^(*)in the LAB color model,thus increase color difference and reduce brightness,the combined effect of color difference and brightness degradation will reduce the color reducibility of CMOS cameras.Therefore,the degradation of the color information of the CMOS camera afterγ-ray irradiation mainly comes from the changes in the FWC and spectral response of CIS,and the spectral transmittance of lens.展开更多
This paper introduces an intelligent computational approach for extracting salient objects fromimages and estimatingtheir distance information with PTZ (Pan-Tilt-Zoom) cameras. PTZ cameras have found wide applications...This paper introduces an intelligent computational approach for extracting salient objects fromimages and estimatingtheir distance information with PTZ (Pan-Tilt-Zoom) cameras. PTZ cameras have found wide applications innumerous public places, serving various purposes such as public securitymanagement, natural disastermonitoring,and crisis alarms, particularly with the rapid development of Artificial Intelligence and global infrastructuralprojects. In this paper, we combine Gauss optical principles with the PTZ camera’s capabilities of horizontal andpitch rotation, as well as optical zoom, to estimate the distance of the object.We present a novel monocular objectdistance estimation model based on the Focal Length-Target Pixel Size (FLTPS) relationship, achieving an accuracyrate of over 95% for objects within a 5 km range. The salient object extraction is achieved through a simplifiedconvolution kernel and the utilization of the object’s RGB features, which offer significantly faster computingspeeds compared to Convolutional Neural Networks (CNNs). Additionally, we introduce the dark channel beforethe fog removal algorithm, resulting in a 20 dB increase in image definition, which significantly benefits distanceestimation. Our system offers the advantages of stability and low device load, making it an asset for public securityaffairs and providing a reference point for future developments in surveillance hardware.展开更多
It is well known that the accuracy of camera calibration is constrained by the size of the reference plate,it is difficult to fabricate large reference plates with high precision.Therefore,it is non-trivial to calibra...It is well known that the accuracy of camera calibration is constrained by the size of the reference plate,it is difficult to fabricate large reference plates with high precision.Therefore,it is non-trivial to calibrate a camera with large field of view(FOV).In this paper,a method is proposed to construct a virtual large reference plate with high precision.Firstly,a high precision datum plane is constructed with a laser interferometer and one-dimensional air guideway,and then the reference plate is positioned at different locations and orientations in the FOV of the camera.The feature points of reference plate are projected to the datum plane to obtain a virtual large reference plate with high-precision.The camera is moved to several positions to get different virtual reference plates,and the camera is calibrated with the virtual reference plates.The experimental results show that the mean re-projection error of the camera calibrated with the proposed method is 0.062 pixels.The length of a scale bar with standard length of 959.778mm was measured with a vision system composed of two calibrated cameras,and the length measurement error is 0.389mm.展开更多
Real-time indoor camera localization is a significant problem in indoor robot navigation and surveillance systems.The scene can change during the image sequence and plays a vital role in the localization performance o...Real-time indoor camera localization is a significant problem in indoor robot navigation and surveillance systems.The scene can change during the image sequence and plays a vital role in the localization performance of robotic applications in terms of accuracy and speed.This research proposed a real-time indoor camera localization system based on a recurrent neural network that detects scene change during the image sequence.An annotated image dataset trains the proposed system and predicts the camera pose in real-time.The system mainly improved the localization performance of indoor cameras by more accurately predicting the camera pose.It also recognizes the scene changes during the sequence and evaluates the effects of these changes.This system achieved high accuracy and real-time performance.The scene change detection process was performed using visual rhythm and the proposed recurrent deep architecture,which performed camera pose prediction and scene change impact evaluation.Overall,this study proposed a novel real-time localization system for indoor cameras that detects scene changes and shows how they affect localization performance.展开更多
Because of its characteristics of simple algorithm and hardware, optical flow-based motion estimation has become a hot research field, especially in GPS-denied environment. Optical flow could be used to obtain the air...Because of its characteristics of simple algorithm and hardware, optical flow-based motion estimation has become a hot research field, especially in GPS-denied environment. Optical flow could be used to obtain the aircraft motion information, but the six-(degree of freedom)(6-DOF) motion still couldn't be accurately estimated by existing methods. The purpose of this work is to provide a motion estimation method based on optical flow from forward and down looking cameras, which doesn't rely on the assumption of level flight. First, the distribution and decoupling method of optical flow from forward camera are utilized to get attitude. Then, the resulted angular velocities are utilized to obtain the translational optical flow of the down camera, which can eliminate the influence of rotational motion on velocity estimation. Besides, the translational motion estimation equation is simplified by establishing the relation between the depths of feature points and the aircraft altitude. Finally, simulation results show that the method presented is accurate and robust.展开更多
This paper describes a multiple camera-based method to reconstruct the 3D shape of a human foot. From a foot database, an initial 3D model of the foot represented by a cloud of points is built. The shape parameters, w...This paper describes a multiple camera-based method to reconstruct the 3D shape of a human foot. From a foot database, an initial 3D model of the foot represented by a cloud of points is built. The shape parameters, which can characterize more than 92% of a foot, are defined by using the principal component analysis method. Then, using "active shape models", the initial 3D model is adapted to the real foot captured in multiple images by applying some constraints (edge points' distance and color variance). We insist here on the experiment part where we demonstrate the efficiency of the proposed method on a plastic foot model, and also on real human feet with various shapes. We propose and compare different ways of texturing the foot which is needed for reconstruction. We present an experiment performed on the plastic foot model and on human feet and propose two different ways to improve the final 3D shapers accuracy according to the previous experiments' results. The first improvement proposed is the densification of the cloud of points used to represent the initial model and the foot database. The second improvement concerns the projected patterns used to texture the foot. We conclude by showing the obtained results for a human foot with the average computed shape error being only 1.06 mm.展开更多
Three-dimensional(3D)modeling is an important topic in computer graphics and computer vision.In recent years,the introduction of consumer-grade depth cameras has resulted in profound advances in 3D modeling.Starting w...Three-dimensional(3D)modeling is an important topic in computer graphics and computer vision.In recent years,the introduction of consumer-grade depth cameras has resulted in profound advances in 3D modeling.Starting with the basic data structure,this survey reviews the latest developments of 3D modeling based on depth cameras,including research works on camera tracking,3D object and scene reconstruction,and high-quality texture reconstruction.We also discuss the future work and possible solutions for 3D modeling based on the depth camera.展开更多
Due to the electronic rolling shutter, high-speed Complementary Metal-Oxide Semiconductor( CMOS) aerial cameras are generally subject to geometric distortions,which cannot be perfectly corrected by conventional vision...Due to the electronic rolling shutter, high-speed Complementary Metal-Oxide Semiconductor( CMOS) aerial cameras are generally subject to geometric distortions,which cannot be perfectly corrected by conventional vision-based algorithms. In this paper we propose a novel approach to address the problem of rolling shutter distortion in aerial imaging. A mathematical model is established by the coordinate transformation method. It can directly calculate the pixel distortion when an aerial camera is imaging at arbitrary gesture angles.Then all pixel distortions form a distortion map over the whole CMOS array and the map is exploited in the image rectification process incorporating reverse projection. The error analysis indicates that within the margin of measuring errors,the final calculation error of our model is less than 1/2 pixel. The experimental results show that our approach yields good rectification performance in a series of images with different distortions. We demonstrate that our method outperforms other vision-based algorithms in terms of the computational complexity,which makes it more suitable for aerial real-time imaging.展开更多
To track human across non-overlapping cameras in depression angles for applications such as multi-airplane visual human tracking and urban multi-camera surveillance,an adaptive human tracking method is proposed,focusi...To track human across non-overlapping cameras in depression angles for applications such as multi-airplane visual human tracking and urban multi-camera surveillance,an adaptive human tracking method is proposed,focusing on both feature representation and human tracking mechanism.Feature representation describes individual by using both improved local appearance descriptors and statistical geometric parameters.The improved feature descriptors can be extracted quickly and make the human feature more discriminative.Adaptive human tracking mechanism is based on feature representation and it arranges the human image blobs in field of view into matrix.Primary appearance models are created to include the maximum inter-camera appearance information captured from different visual angles.The persons appeared in camera are first filtered by statistical geometric parameters.Then the one among the filtered persons who has the maximum matching scale with the primary models is determined to be the target person.Subsequently,the image blobs of the target person are used to update and generate new primary appearance models for the next camera,thus being robust to visual angle changes.Experimental results prove the excellence of the feature representation and show the good generalization capability of tracking mechanism as well as its robustness to condition variables.展开更多
AIM:To examine performances regarding prediction of polyp histology using high-definition (HD) i-scan in a group of endoscopists with varying levels of experience. METHODS:We used a digital library of HD i-scan still ...AIM:To examine performances regarding prediction of polyp histology using high-definition (HD) i-scan in a group of endoscopists with varying levels of experience. METHODS:We used a digital library of HD i-scan still images, comprising twin pictures (surface enhancement and tone enhancement), collected at our university hospital. We defined endoscopic features of adenomatous and non-adenomatous polyps, according to the following parameters:color, surface pattern and vascular pattern. We familiarized the participating endoscopists on optical diagnosis of colorectal polyps using a 20-min didactic training session. All endoscopists were asked to evaluate an image set of 50 colorectal polyps with regard to polyp histology. We classified the diagnoses into high confidence (i.e., cases in which the endoscopist could assign a diagnosis with certainty) and low confidence diagnoses (i.e., cases in which the endoscopist preferred to send the polyp for formal histology). Mean sensitivity, specificity and accuracy per endoscopist/image were computed and differences between groups tested using independent-samples t tests. High vs low confidence diagnoses were compared using the pairedsamples t test. RESULTS:Eleven endoscopists without previous experience on optical diagnosis evaluated a total of 550 images (396 adenomatous, 154 non-adenomatous). Mean sensitivity, specificity and accuracy for diagnosing adenomas were 79.3%, 85.7% and 81.1%, respectively. No significant differences were found between gastroenterologists and trainees regarding performances of optical diagnosis (mean accuracy 78.0%vs 82.9%,P = 0.098). Diminutive lesions were predicted with a lower mean accuracy as compared to non-diminutive lesions (74.2% vs 93.1%, P = 0.008). A total of 446 (81.1%) diagnoses were made with high confidence. High confidence diagnoses corresponded to a significantly higher mean accuracy than low confidence diagnoses (84.0% vs 64.3%, P = 0.008). A total of 319 (58.0%) images were evaluated as having excellent quality. Considering excellent quality images in conjunction with high confidence diagnosis, overall accuracy increased to 92.8%. CONCLUSION:After a single training session, endoscopists with varying levels of experience can already provide optical diagnosis with an accuracy of 84.0%.展开更多
AIM:To explore the feasibility of dual camera capsule (DCC)small-bowel(SB)imaging and to examine if two cameras complement each other to detect more SB lesions.METHODS:Forty-one eligible,consecutive patients underwent...AIM:To explore the feasibility of dual camera capsule (DCC)small-bowel(SB)imaging and to examine if two cameras complement each other to detect more SB lesions.METHODS:Forty-one eligible,consecutive patients underwent DCC SB imaging.Two experienced investigators examined the videos and compared the total number of detected lesions to the number of lesions detected by each camera separately.Examination tolerability was assessed using a questionnaire.RESULTS:One patient was excluded.DCC cameras detected 68 positive findings(POS)in 20(50%)cases.Fifty of them were detected by the"yellow"camera,48 by the"green"and 28 by both cameras;44%(n=22)of the"yellow"camera’s POS were not detected by the"green"camera and 42%(n=20)of the"green" camera’s POS were not detected by the"yellow"camera.In two cases,only one camera detected significant findings.All participants had 216 findings of unknown significance(FUS).The"yellow","green"and both cameras detected 171,161,and 116 FUS,respectively;32%(n=55)of the"yellow"camera’s FUS were not detected by the"green"camera and 28%(n=45)of the"green"camera’s FUS were not detected by the "yellow"camera.There were no complications related to the examination,and 97.6%of the patients would repeat the examination,if necessary.CONCLUSION:DCC SB examination is feasible and well tolerated.The two cameras complement each other to detect more SB lesions.展开更多
Compton camera-based prompt gamma(PG) imaging has been proposed for range verification during proton therapy. However, a deviation between the PG and dose distributions, as well as the difference between the reconstru...Compton camera-based prompt gamma(PG) imaging has been proposed for range verification during proton therapy. However, a deviation between the PG and dose distributions, as well as the difference between the reconstructed PG and exact values, limit the effectiveness of the approach in accurate range monitoring during clinical applications. The aim of the study was to realize a PG-based dose reconstruction with a Compton camera, thereby further improving the prediction accuracy of in vivo range verification and providing a novel method for beam monitoring during proton therapy. In this paper, we present an approach based on a subset-driven origin ensemble with resolution recovery and a double evolutionary algorithm to reconstruct the dose depth profile(DDP) from the gamma events obtained by a cadmium-zinc-telluride Compton camera with limited position and energy resolution. Simulations of proton pencil beams with clinical particle rate irradiating phantoms made of different materials and the CT-based thoracic phantom were used to evaluate the feasibility of the proposed method. The results show that for the monoenergetic proton pencil beam irradiating homogeneous-material box phantom,the accuracy of the reconstructed DDP was within 0.3 mm for range prediction and within 5.2% for dose prediction. In particular, for 1.6-Gy irradiation in the therapy simulation of thoracic tumors, the range deviation of the reconstructed spreadout Bragg peak was within 0.8 mm, and the relative dose deviation in the peak area was less than 7% compared to the exact values. The results demonstrate the potential and feasibility of the proposed method in future Compton-based accurate dose reconstruction and range verification during proton therapy.展开更多
To enhance the image motion compensation accuracy of off-axis three-mirror anastigmatic( TMA)three-line array aerospace mapping cameras,a new method of image motion velocity field modeling is proposed in this paper. F...To enhance the image motion compensation accuracy of off-axis three-mirror anastigmatic( TMA)three-line array aerospace mapping cameras,a new method of image motion velocity field modeling is proposed in this paper. Firstly,based on the imaging principle of mapping cameras,an analytical expression of image motion velocity of off-axis TMA three-line array aerospace mapping cameras is deduced from different coordinate systems we established and the attitude dynamics principle. Then,the case of a three-line array mapping camera is studied,in which the simulation of the focal plane image motion velocity fields of the forward-view camera,the nadir-view camera and the backward-view camera are carried out,and the optimization schemes for image motion velocity matching and drift angle matching are formulated according the simulation results. Finally,this method is verified with a dynamic imaging experimental system. The results are indicative of that when image motion compensation for nadir-view camera is conducted using the proposed image motion velocity field model,the line pair of target images at Nyquist frequency is clear and distinguishable. Under the constraint that modulation transfer function( MTF) reduces by 5%,when the horizontal frequencies of the forward-view camera and the backward-view camera are adjusted uniformly according to the proposed image motion velocity matching scheme,the time delay integration( TDI) stages reach 6 at most. When the TDI stages are more than 6,the three groups of camera will independently undergo horizontal frequency adjustment. However, when the proposed drift angle matching scheme is adopted for uniform drift angle adjustment,the number of TDI stages will not exceed 81. The experimental results have demonstrated the validity and accuracy of the proposed image motion velocity field model and matching optimization scheme,providing reliable basis for on-orbit image motion compensation of aerospace mapping cameras.展开更多
A novel and fast three-dimensional reconstruction method for a Compton camera and its performance in radionuclide imaging is proposed and analyzed in this study. The conical surface sampling back-projection method wit...A novel and fast three-dimensional reconstruction method for a Compton camera and its performance in radionuclide imaging is proposed and analyzed in this study. The conical surface sampling back-projection method with scattering angle correction(CSS-BP-SC) can quickly perform the back-projection process of the Compton cone and can be used to precompute the list-mode maximum likelihood expectation maximization(LM-MLEM). A dedicated parallel architecture was designed for the graphics processing unit acceleration of the back-projection and iteration stage of the CSS-BP-SC-based LM-MLEM. The imaging results of the two-point source Monte Carlo(MC) simulation demonstrate that by analyzing the full width at half maximum along the three coordinate axes, the CSS-BP-SC-based LM-MLEM can obtain imaging results comparable to those of the traditional reconstruction algorithm, that is, the simple back-projection-based LM-MLEM. The imaging results of the mouse phantom MC simulation and experiment demonstrate that the reconstruction results obtained by the proposed method sufficiently coincide with the set radioactivity distribution, and the speed increased by more than 664 times compared to the traditional reconstruction algorithm in the mouse phantom experiment. The proposed method will further advance the imaging applications of Compton cameras.展开更多
基金National Natural Science Foundation of China(11805269)West Light Talent Training Plan of the Chinese Academy of Sciences(2022-XBQNXZ-010)Science and Technology Innovation Leading Talent Project of Xinjiang Uygur Autonomous Region(2022TSYCLJ0042)。
文摘Theγ-rays are widely and abundantly present in strong nuclear radiation environments,and when they act on the camera equipment used to obtain environmental visual information on nuclear robots,radiation effects will occur,which will degrade the performance of the camera system,reduce the imaging quality,and even cause catastrophic consequences.Color reducibility is an important index for evaluating the imaging quality of color camera,but its degradation mechanism in a nuclear radiation environment is still unclear.In this paper,theγ-ray irradiation experiments of CMOS cameras were carried out to analyse the degradation law of the camera’s color reducibility with cumulative irradiation and reveal the degradation mechanism of the color information of the CMOS camera underγ-ray irradiation.The results show that the spectral response of CMOS image sensor(CIS)and the spectral transmittance of lens after irradiation affect the values of a^(*)and b^(*)in the LAB color model.While the full well capacity(FWC)of CIS and transmittance of lens affect the value of L^(*)in the LAB color model,thus increase color difference and reduce brightness,the combined effect of color difference and brightness degradation will reduce the color reducibility of CMOS cameras.Therefore,the degradation of the color information of the CMOS camera afterγ-ray irradiation mainly comes from the changes in the FWC and spectral response of CIS,and the spectral transmittance of lens.
基金the Social Development Project of Jiangsu Key R&D Program(BE2022680)the National Natural Science Foundation of China(Nos.62371253,52278119).
文摘This paper introduces an intelligent computational approach for extracting salient objects fromimages and estimatingtheir distance information with PTZ (Pan-Tilt-Zoom) cameras. PTZ cameras have found wide applications innumerous public places, serving various purposes such as public securitymanagement, natural disastermonitoring,and crisis alarms, particularly with the rapid development of Artificial Intelligence and global infrastructuralprojects. In this paper, we combine Gauss optical principles with the PTZ camera’s capabilities of horizontal andpitch rotation, as well as optical zoom, to estimate the distance of the object.We present a novel monocular objectdistance estimation model based on the Focal Length-Target Pixel Size (FLTPS) relationship, achieving an accuracyrate of over 95% for objects within a 5 km range. The salient object extraction is achieved through a simplifiedconvolution kernel and the utilization of the object’s RGB features, which offer significantly faster computingspeeds compared to Convolutional Neural Networks (CNNs). Additionally, we introduce the dark channel beforethe fog removal algorithm, resulting in a 20 dB increase in image definition, which significantly benefits distanceestimation. Our system offers the advantages of stability and low device load, making it an asset for public securityaffairs and providing a reference point for future developments in surveillance hardware.
文摘It is well known that the accuracy of camera calibration is constrained by the size of the reference plate,it is difficult to fabricate large reference plates with high precision.Therefore,it is non-trivial to calibrate a camera with large field of view(FOV).In this paper,a method is proposed to construct a virtual large reference plate with high precision.Firstly,a high precision datum plane is constructed with a laser interferometer and one-dimensional air guideway,and then the reference plate is positioned at different locations and orientations in the FOV of the camera.The feature points of reference plate are projected to the datum plane to obtain a virtual large reference plate with high-precision.The camera is moved to several positions to get different virtual reference plates,and the camera is calibrated with the virtual reference plates.The experimental results show that the mean re-projection error of the camera calibrated with the proposed method is 0.062 pixels.The length of a scale bar with standard length of 959.778mm was measured with a vision system composed of two calibrated cameras,and the length measurement error is 0.389mm.
文摘Real-time indoor camera localization is a significant problem in indoor robot navigation and surveillance systems.The scene can change during the image sequence and plays a vital role in the localization performance of robotic applications in terms of accuracy and speed.This research proposed a real-time indoor camera localization system based on a recurrent neural network that detects scene change during the image sequence.An annotated image dataset trains the proposed system and predicts the camera pose in real-time.The system mainly improved the localization performance of indoor cameras by more accurately predicting the camera pose.It also recognizes the scene changes during the sequence and evaluates the effects of these changes.This system achieved high accuracy and real-time performance.The scene change detection process was performed using visual rhythm and the proposed recurrent deep architecture,which performed camera pose prediction and scene change impact evaluation.Overall,this study proposed a novel real-time localization system for indoor cameras that detects scene changes and shows how they affect localization performance.
基金Project(2012CB720003)supported by the National Basic Research Program of ChinaProjects(61320106010,61127007,61121003,61573019)supported by the National Natural Science Foundation of ChinaProject(2013DFE13040)supported by the Special Program for International Science and Technology Cooperation from Ministry of Science and Technology of China
文摘Because of its characteristics of simple algorithm and hardware, optical flow-based motion estimation has become a hot research field, especially in GPS-denied environment. Optical flow could be used to obtain the aircraft motion information, but the six-(degree of freedom)(6-DOF) motion still couldn't be accurately estimated by existing methods. The purpose of this work is to provide a motion estimation method based on optical flow from forward and down looking cameras, which doesn't rely on the assumption of level flight. First, the distribution and decoupling method of optical flow from forward camera are utilized to get attitude. Then, the resulted angular velocities are utilized to obtain the translational optical flow of the down camera, which can eliminate the influence of rotational motion on velocity estimation. Besides, the translational motion estimation equation is simplified by establishing the relation between the depths of feature points and the aircraft altitude. Finally, simulation results show that the method presented is accurate and robust.
基金This work was supported by Grant-in-Aid for Scientific Research (C) (No.17500119)
文摘This paper describes a multiple camera-based method to reconstruct the 3D shape of a human foot. From a foot database, an initial 3D model of the foot represented by a cloud of points is built. The shape parameters, which can characterize more than 92% of a foot, are defined by using the principal component analysis method. Then, using "active shape models", the initial 3D model is adapted to the real foot captured in multiple images by applying some constraints (edge points' distance and color variance). We insist here on the experiment part where we demonstrate the efficiency of the proposed method on a plastic foot model, and also on real human feet with various shapes. We propose and compare different ways of texturing the foot which is needed for reconstruction. We present an experiment performed on the plastic foot model and on human feet and propose two different ways to improve the final 3D shapers accuracy according to the previous experiments' results. The first improvement proposed is the densification of the cloud of points used to represent the initial model and the foot database. The second improvement concerns the projected patterns used to texture the foot. We conclude by showing the obtained results for a human foot with the average computed shape error being only 1.06 mm.
基金Supported by National Natural Science Foundation of China (60575019), the National High Technology Research and Development Program of China (863 Program) (2006AA01Zl16), and Institute of Automation Chinese Academy of Sciences Innovation Fund For Young Scientists
基金National Natural Science Foundation of China(61732016).
文摘Three-dimensional(3D)modeling is an important topic in computer graphics and computer vision.In recent years,the introduction of consumer-grade depth cameras has resulted in profound advances in 3D modeling.Starting with the basic data structure,this survey reviews the latest developments of 3D modeling based on depth cameras,including research works on camera tracking,3D object and scene reconstruction,and high-quality texture reconstruction.We also discuss the future work and possible solutions for 3D modeling based on the depth camera.
基金Sponsored by the National Natural Science Foundation of China(Grant No.60902067)the Foundation for Science & Technology Research Project of Jilin Province(Grant No.11ZDGG001)
文摘Due to the electronic rolling shutter, high-speed Complementary Metal-Oxide Semiconductor( CMOS) aerial cameras are generally subject to geometric distortions,which cannot be perfectly corrected by conventional vision-based algorithms. In this paper we propose a novel approach to address the problem of rolling shutter distortion in aerial imaging. A mathematical model is established by the coordinate transformation method. It can directly calculate the pixel distortion when an aerial camera is imaging at arbitrary gesture angles.Then all pixel distortions form a distortion map over the whole CMOS array and the map is exploited in the image rectification process incorporating reverse projection. The error analysis indicates that within the margin of measuring errors,the final calculation error of our model is less than 1/2 pixel. The experimental results show that our approach yields good rectification performance in a series of images with different distortions. We demonstrate that our method outperforms other vision-based algorithms in terms of the computational complexity,which makes it more suitable for aerial real-time imaging.
基金funded by the Natural Science Foundation of Jiangsu Province(No.BK2012389)the National Natural Science Foundation of China(Nos.71303110,91024024)the Foundation of Graduate Innovation Center in NUAA(Nos.kfjj201471,kfjj201473)
文摘To track human across non-overlapping cameras in depression angles for applications such as multi-airplane visual human tracking and urban multi-camera surveillance,an adaptive human tracking method is proposed,focusing on both feature representation and human tracking mechanism.Feature representation describes individual by using both improved local appearance descriptors and statistical geometric parameters.The improved feature descriptors can be extracted quickly and make the human feature more discriminative.Adaptive human tracking mechanism is based on feature representation and it arranges the human image blobs in field of view into matrix.Primary appearance models are created to include the maximum inter-camera appearance information captured from different visual angles.The persons appeared in camera are first filtered by statistical geometric parameters.Then the one among the filtered persons who has the maximum matching scale with the primary models is determined to be the target person.Subsequently,the image blobs of the target person are used to update and generate new primary appearance models for the next camera,thus being robust to visual angle changes.Experimental results prove the excellence of the feature representation and show the good generalization capability of tracking mechanism as well as its robustness to condition variables.
文摘AIM:To examine performances regarding prediction of polyp histology using high-definition (HD) i-scan in a group of endoscopists with varying levels of experience. METHODS:We used a digital library of HD i-scan still images, comprising twin pictures (surface enhancement and tone enhancement), collected at our university hospital. We defined endoscopic features of adenomatous and non-adenomatous polyps, according to the following parameters:color, surface pattern and vascular pattern. We familiarized the participating endoscopists on optical diagnosis of colorectal polyps using a 20-min didactic training session. All endoscopists were asked to evaluate an image set of 50 colorectal polyps with regard to polyp histology. We classified the diagnoses into high confidence (i.e., cases in which the endoscopist could assign a diagnosis with certainty) and low confidence diagnoses (i.e., cases in which the endoscopist preferred to send the polyp for formal histology). Mean sensitivity, specificity and accuracy per endoscopist/image were computed and differences between groups tested using independent-samples t tests. High vs low confidence diagnoses were compared using the pairedsamples t test. RESULTS:Eleven endoscopists without previous experience on optical diagnosis evaluated a total of 550 images (396 adenomatous, 154 non-adenomatous). Mean sensitivity, specificity and accuracy for diagnosing adenomas were 79.3%, 85.7% and 81.1%, respectively. No significant differences were found between gastroenterologists and trainees regarding performances of optical diagnosis (mean accuracy 78.0%vs 82.9%,P = 0.098). Diminutive lesions were predicted with a lower mean accuracy as compared to non-diminutive lesions (74.2% vs 93.1%, P = 0.008). A total of 446 (81.1%) diagnoses were made with high confidence. High confidence diagnoses corresponded to a significantly higher mean accuracy than low confidence diagnoses (84.0% vs 64.3%, P = 0.008). A total of 319 (58.0%) images were evaluated as having excellent quality. Considering excellent quality images in conjunction with high confidence diagnosis, overall accuracy increased to 92.8%. CONCLUSION:After a single training session, endoscopists with varying levels of experience can already provide optical diagnosis with an accuracy of 84.0%.
文摘AIM:To explore the feasibility of dual camera capsule (DCC)small-bowel(SB)imaging and to examine if two cameras complement each other to detect more SB lesions.METHODS:Forty-one eligible,consecutive patients underwent DCC SB imaging.Two experienced investigators examined the videos and compared the total number of detected lesions to the number of lesions detected by each camera separately.Examination tolerability was assessed using a questionnaire.RESULTS:One patient was excluded.DCC cameras detected 68 positive findings(POS)in 20(50%)cases.Fifty of them were detected by the"yellow"camera,48 by the"green"and 28 by both cameras;44%(n=22)of the"yellow"camera’s POS were not detected by the"green"camera and 42%(n=20)of the"green" camera’s POS were not detected by the"yellow"camera.In two cases,only one camera detected significant findings.All participants had 216 findings of unknown significance(FUS).The"yellow","green"and both cameras detected 171,161,and 116 FUS,respectively;32%(n=55)of the"yellow"camera’s FUS were not detected by the"green"camera and 28%(n=45)of the"green"camera’s FUS were not detected by the "yellow"camera.There were no complications related to the examination,and 97.6%of the patients would repeat the examination,if necessary.CONCLUSION:DCC SB examination is feasible and well tolerated.The two cameras complement each other to detect more SB lesions.
基金supported by Natural Science Foundation of Beijing Municipality (Beijing Natural Science Foundation)(No.7191005)。
文摘Compton camera-based prompt gamma(PG) imaging has been proposed for range verification during proton therapy. However, a deviation between the PG and dose distributions, as well as the difference between the reconstructed PG and exact values, limit the effectiveness of the approach in accurate range monitoring during clinical applications. The aim of the study was to realize a PG-based dose reconstruction with a Compton camera, thereby further improving the prediction accuracy of in vivo range verification and providing a novel method for beam monitoring during proton therapy. In this paper, we present an approach based on a subset-driven origin ensemble with resolution recovery and a double evolutionary algorithm to reconstruct the dose depth profile(DDP) from the gamma events obtained by a cadmium-zinc-telluride Compton camera with limited position and energy resolution. Simulations of proton pencil beams with clinical particle rate irradiating phantoms made of different materials and the CT-based thoracic phantom were used to evaluate the feasibility of the proposed method. The results show that for the monoenergetic proton pencil beam irradiating homogeneous-material box phantom,the accuracy of the reconstructed DDP was within 0.3 mm for range prediction and within 5.2% for dose prediction. In particular, for 1.6-Gy irradiation in the therapy simulation of thoracic tumors, the range deviation of the reconstructed spreadout Bragg peak was within 0.8 mm, and the relative dose deviation in the peak area was less than 7% compared to the exact values. The results demonstrate the potential and feasibility of the proposed method in future Compton-based accurate dose reconstruction and range verification during proton therapy.
基金Sponsored by the National High Technology Research and Development Program of China(Grant No.863-2-5-1-13B)the Jilin Province Science and Technology Development Plan Item(Grant No.20130522107JH)
文摘To enhance the image motion compensation accuracy of off-axis three-mirror anastigmatic( TMA)three-line array aerospace mapping cameras,a new method of image motion velocity field modeling is proposed in this paper. Firstly,based on the imaging principle of mapping cameras,an analytical expression of image motion velocity of off-axis TMA three-line array aerospace mapping cameras is deduced from different coordinate systems we established and the attitude dynamics principle. Then,the case of a three-line array mapping camera is studied,in which the simulation of the focal plane image motion velocity fields of the forward-view camera,the nadir-view camera and the backward-view camera are carried out,and the optimization schemes for image motion velocity matching and drift angle matching are formulated according the simulation results. Finally,this method is verified with a dynamic imaging experimental system. The results are indicative of that when image motion compensation for nadir-view camera is conducted using the proposed image motion velocity field model,the line pair of target images at Nyquist frequency is clear and distinguishable. Under the constraint that modulation transfer function( MTF) reduces by 5%,when the horizontal frequencies of the forward-view camera and the backward-view camera are adjusted uniformly according to the proposed image motion velocity matching scheme,the time delay integration( TDI) stages reach 6 at most. When the TDI stages are more than 6,the three groups of camera will independently undergo horizontal frequency adjustment. However, when the proposed drift angle matching scheme is adopted for uniform drift angle adjustment,the number of TDI stages will not exceed 81. The experimental results have demonstrated the validity and accuracy of the proposed image motion velocity field model and matching optimization scheme,providing reliable basis for on-orbit image motion compensation of aerospace mapping cameras.
基金supported by the National Natural Science Foundation of China (No. 12220101005)Natural Science Foundation of Jiangsu Province (No. BK20220132)+2 种基金Primary Research and Development Plan of Jiangsu Province (No. BE2019002-3)Fundamental Research Funds for Central Universities (No. NG2022004)the Foundation of the Graduate Innovation Center in NUAA (No. xcxjh20210613)。
文摘A novel and fast three-dimensional reconstruction method for a Compton camera and its performance in radionuclide imaging is proposed and analyzed in this study. The conical surface sampling back-projection method with scattering angle correction(CSS-BP-SC) can quickly perform the back-projection process of the Compton cone and can be used to precompute the list-mode maximum likelihood expectation maximization(LM-MLEM). A dedicated parallel architecture was designed for the graphics processing unit acceleration of the back-projection and iteration stage of the CSS-BP-SC-based LM-MLEM. The imaging results of the two-point source Monte Carlo(MC) simulation demonstrate that by analyzing the full width at half maximum along the three coordinate axes, the CSS-BP-SC-based LM-MLEM can obtain imaging results comparable to those of the traditional reconstruction algorithm, that is, the simple back-projection-based LM-MLEM. The imaging results of the mouse phantom MC simulation and experiment demonstrate that the reconstruction results obtained by the proposed method sufficiently coincide with the set radioactivity distribution, and the speed increased by more than 664 times compared to the traditional reconstruction algorithm in the mouse phantom experiment. The proposed method will further advance the imaging applications of Compton cameras.