The inter-class face classification problem is more reasonable than the intra-class classification problem.To address this issue,we have carried out empirical research on classifying Indian people to their geographica...The inter-class face classification problem is more reasonable than the intra-class classification problem.To address this issue,we have carried out empirical research on classifying Indian people to their geographical regions.This work aimed to construct a computational classification model for classifying Indian regional face images acquired from south and east regions of India,referring to human vision.We have created an Automated Human Intelligence System(AHIS)to evaluate human visual capabilities.Analysis of AHIS response showed that face shape is a discriminative feature among the other facial features.We have developed a modified convolutional neural network to characterize the human vision response to improve face classification accuracy.The proposed model achieved mean F1 and Matthew Correlation Coefficient(MCC)of 0.92 and 0.84,respectively,on the validation set,outperforming the traditional Convolutional Neural Network(CNN).The CNN-Contoured Face(CNN-FC)model is developed to train contoured face images to investigate the influence of face shape.Finally,to cross-validate the accuracy of these models,the traditional CNN model is trained on the same dataset.With an accuracy of 92.98%,the Modified-CNN(M-CNN)model has demonstrated that the proposed method could facilitate the tangible impact in intra-classification problems.A novel Indian regional face dataset is created for supporting this supervised classification work,and it will be available to the research community.展开更多
Prompt radiation emitted during accelerator operation poses a significant health risk,necessitating a thorough search and securing of hazardous areas prior to initiation.Currently,manual sweep methods are employed.How...Prompt radiation emitted during accelerator operation poses a significant health risk,necessitating a thorough search and securing of hazardous areas prior to initiation.Currently,manual sweep methods are employed.However,the limitations of manual sweeps have become increasingly evident with the implementation of large-scale accelerators.By leveraging advancements in machine vision technology,the automatic identification of stranded personnel in controlled areas through camera imagery presents a viable solution for efficient search and security.Given the criticality of personal safety for stranded individuals,search and security processes must be sufficiently reliable.To ensure comprehensive coverage,180°camera groups were strategically positioned on both sides of the accelerator tunnel to eliminate blind spots within the monitoring range.The YOLOV8 network model was modified to enable the detection of small targets,such as hands and feet,as well as larger targets formed by individuals near the cameras.Furthermore,the system incorporates a pedestrian recognition model that detects human body parts,and an information fusion strategy is used to integrate the detected head,hands,and feet with the identified pedestrians as a cohesive unit.This strategy enhanced the capability of the model to identify pedestrians obstructed by equipment,resulting in a notable improvement in the recall rate.Specifically,recall rates of 0.915 and 0.82were obtained for Datasets 1 and 2,respectively.Although there was a slight decrease in accuracy,it aligned with the intended purpose of the search-and-secure software design.Experimental tests conducted within an accelerator tunnel demonstrated the effectiveness of this approach in achieving reliable recognition outcomes.展开更多
The human pose paradigm is estimated using a transformer-based multi-branch multidimensional directed the three-dimensional(3D)method that takes into account self-occlusion,badly posedness,and a lack of depth data in ...The human pose paradigm is estimated using a transformer-based multi-branch multidimensional directed the three-dimensional(3D)method that takes into account self-occlusion,badly posedness,and a lack of depth data in the per-frame 3D posture estimation from two-dimensional(2D)mapping to 3D mapping.Firstly,by examining the relationship between the movements of different bones in the human body,four virtual skeletons are proposed to enhance the cyclic constraints of limb joints.Then,multiple parameters describing the skeleton are fused and projected into a high-dimensional space.Utilizing a multi-branch network,motion features between bones and overall motion features are extracted to mitigate the drift error in the estimation results.Furthermore,the estimated relative depth is projected into 3D space,and the error is calculated against real 3D data,forming a loss function along with the relative depth error.This article adopts the average joint pixel error as the primary performance metric.Compared to the benchmark approach,the estimation findings indicate an increase in average precision of 1.8 mm within the Human3.6M sample.展开更多
This paper presents discrete wavelet transform （DWT） and its inverse （IDWT） with Haar wavelets as tools to compute the variable size interpolated versions of an image at optimum computational load. As a human obse...This paper presents discrete wavelet transform （DWT） and its inverse （IDWT） with Haar wavelets as tools to compute the variable size interpolated versions of an image at optimum computational load. As a human observer moves closer to or farther from a scene, the retinal image of the scene zooms in or out, respectively. This zooming in or out can be modeled using variable scale interpolation. The paper proposes a novel way of applying DWT and IDWT in a piecewise manner by non-uniform down- or up-sampling of the images to achieve partially sampled versions of the images. The partially sampled versions are then aggregated to achieve the final variable scale interpolated images. The non-uniform down- or up-sampling here is a function of the required scale of interpolation. Appropriate zero padding is used to make the images suitable for the required non-uniform sampling and the subsequent interpolation to the required scale. The concept of zeroeth level DWT is introduced here, which works as the basis for interpolating the images to achieve bigger size than the original one. The main emphasis here is on the computation of variable size images at less computational load, without compromise of quality of images. The interpolated images to different sizes and the reconstructed images are benchmarked using the statistical parameters and visual comparison. It has been found that the proposed approach performs better as compared to bilinear and bicubic interpolation techniques.展开更多
This article introduced the vision building concept about human influenza pandemic prevention and control.Different visions were built by creating different shapes of building blocks which also represented different o...This article introduced the vision building concept about human influenza pandemic prevention and control.Different visions were built by creating different shapes of building blocks which also represented different organizations and physical facilities,respectively.The around-view reflection is required to be developed in the process of building so as to search for the ideal pattern.The correlation of all sectors and systems are established to combine different kinds of things,from one family to another,from communities,towns,counties,cities,rural areas, provinces to the state to handle trivial problems.These training objectives have been successfully accomplished,which has not only enriched the knowledge about prevention and control of influenza pandemic between different departments but also clarified the roles and responsibility. It lays the firm foundation for next cooperation between different departments,and make a bridge for the objective and choice of channel over human influenza pandemic prevention and control.展开更多
Having proper sanitation and hygiene, access to affordable health care and enough food on the table are the basic conditions for a dignified life. This link between human dignity and the right to development was made ...Having proper sanitation and hygiene, access to affordable health care and enough food on the table are the basic conditions for a dignified life. This link between human dignity and the right to development was made very persuasively already in the White Paper on human rights, issued by the State Council of P.R.C. in 1991. The Declaration on the right to development can be considered the first successful joint action undertaken by Southern states in the area of human rights. The Declaration was based on Southern scholarship, such as the pioneering research conducted by the Senegalese jurist Kéba M’baye. And its adoption was the result of joint stage management performed by diplomats from different continents. Therefore the Declaration serves as a source of inspiration for the work of drafting a Comprehensive Southern Vision on human rights. The Vision document will lay out a common Southern outlook on human rights issues as an elaboration of the Universal Declaration.展开更多
The aim of this paper is to create an interface for human-robot interaction.Specifically,musical performance parameters(i.e.vibrato expression)of the Waseda Flutist Robot No.4 Refined IV(WF-4RIV)are to be manipulated....The aim of this paper is to create an interface for human-robot interaction.Specifically,musical performance parameters(i.e.vibrato expression)of the Waseda Flutist Robot No.4 Refined IV(WF-4RIV)are to be manipulated.This research focused on enabling the WF-4RIV to interact with human players(musicians)in a natural way.In this paper,as the first approach,a vision processing algorithm,which is able to track the 3D-orientation and position of a musical instrument,was developed.In particular,the robot acquires image data through two cameras attached to its head.Using color histogram matching and a particle filter,the position of the musician's hands on the instrument are tracked.Analysis of this data determines orientation and location of the instrument.These parameters are mapped to manipulate the musical expression of the WF-4RIV,more specifically sound vibrato and volume values.The authors present preliminary experiments to determine if the robot may dynamically change musical parameters while interacting with a human player(i.e.vibrato etc.).From the experimental results,they may confirm the feasibility of the interaction during the performance,although further research must be carried out to consider the physical constraints of the flutist robot.展开更多
This paper presents some human-inspired strategies for lighting control in a robot system for best scene interpretation,where the main intention is to avoid possible glares or highlights occurring in images. It firstl...This paper presents some human-inspired strategies for lighting control in a robot system for best scene interpretation,where the main intention is to avoid possible glares or highlights occurring in images. It firstly compares the characteristics of human eyes and robot eyes. Then some evaluation criteria are addressed to assess the lighting conditions. A bio-inspired method is adopted to avoid the visual glare which is caused by either direct illumination from large light sources or indirect illumination reflected by smooth surfaces. Appropriate methods are proposed to optimize the pose and optical parameters of the light source and the vision camera.展开更多
A shadow detection method using pulse couple neural network inspired by the characters of human visual system is proposed.More precisely,lateral inhibition of human vision and coefficient of variation are combined tog...A shadow detection method using pulse couple neural network inspired by the characters of human visual system is proposed.More precisely,lateral inhibition of human vision and coefficient of variation are combined together to improve the pulse couple neural network.Shadow detection is considered to be a shadow region segmentation problem.Experiment shows that the presented method is consistent with human vision compared to shadow detection methods based on HSV and pulse couple neural network(PCNN) by both subjective and objective assessments.展开更多
Human recognition technology based on biometrics has become a fundamental requirement in all aspects of life due to increased concerns about security and privacy issues.Therefore,biometric systems have emerged as a te...Human recognition technology based on biometrics has become a fundamental requirement in all aspects of life due to increased concerns about security and privacy issues.Therefore,biometric systems have emerged as a technology with the capability to identify or authenticate individuals based on their physiological and behavioral characteristics.Among different viable biometric modalities,the human ear structure can offer unique and valuable discriminative characteristics for human recognition systems.In recent years,most existing traditional ear recognition systems have been designed based on computer vision models and have achieved successful results.Nevertheless,such traditional models can be sensitive to several unconstrained environmental factors.As such,some traits may be difficult to extract automatically but can still be semantically perceived as soft biometrics.This research proposes a new group of semantic features to be used as soft ear biometrics,mainly inspired by conventional descriptive traits used naturally by humans when identifying or describing each other.Hence,the research study is focused on the fusion of the soft ear biometric traits with traditional(hard)ear biometric features to investigate their validity and efficacy in augmenting human identification performance.The proposed framework has two subsystems:first,a computer vision-based subsystem,extracting traditional(hard)ear biometric traits using principal component analysis(PCA)and local binary patterns(LBP),and second,a crowdsourcing-based subsystem,deriving semantic(soft)ear biometric traits.Several feature-level fusion experiments were conducted using the AMI database to evaluate the proposed algorithm’s performance.The obtained results for both identification and verification showed that the proposed soft ear biometric information significantly improved the recognition performance of traditional ear biometrics,reaching up to 12%for LBP and 5%for PCA descriptors;when fusing all three capacities PCA,LBP,and soft traits using k-nearest neighbors(KNN)classifier.展开更多
文摘The inter-class face classification problem is more reasonable than the intra-class classification problem.To address this issue,we have carried out empirical research on classifying Indian people to their geographical regions.This work aimed to construct a computational classification model for classifying Indian regional face images acquired from south and east regions of India,referring to human vision.We have created an Automated Human Intelligence System(AHIS)to evaluate human visual capabilities.Analysis of AHIS response showed that face shape is a discriminative feature among the other facial features.We have developed a modified convolutional neural network to characterize the human vision response to improve face classification accuracy.The proposed model achieved mean F1 and Matthew Correlation Coefficient(MCC)of 0.92 and 0.84,respectively,on the validation set,outperforming the traditional Convolutional Neural Network(CNN).The CNN-Contoured Face(CNN-FC)model is developed to train contoured face images to investigate the influence of face shape.Finally,to cross-validate the accuracy of these models,the traditional CNN model is trained on the same dataset.With an accuracy of 92.98%,the Modified-CNN(M-CNN)model has demonstrated that the proposed method could facilitate the tangible impact in intra-classification problems.A novel Indian regional face dataset is created for supporting this supervised classification work,and it will be available to the research community.
文摘Prompt radiation emitted during accelerator operation poses a significant health risk,necessitating a thorough search and securing of hazardous areas prior to initiation.Currently,manual sweep methods are employed.However,the limitations of manual sweeps have become increasingly evident with the implementation of large-scale accelerators.By leveraging advancements in machine vision technology,the automatic identification of stranded personnel in controlled areas through camera imagery presents a viable solution for efficient search and security.Given the criticality of personal safety for stranded individuals,search and security processes must be sufficiently reliable.To ensure comprehensive coverage,180°camera groups were strategically positioned on both sides of the accelerator tunnel to eliminate blind spots within the monitoring range.The YOLOV8 network model was modified to enable the detection of small targets,such as hands and feet,as well as larger targets formed by individuals near the cameras.Furthermore,the system incorporates a pedestrian recognition model that detects human body parts,and an information fusion strategy is used to integrate the detected head,hands,and feet with the identified pedestrians as a cohesive unit.This strategy enhanced the capability of the model to identify pedestrians obstructed by equipment,resulting in a notable improvement in the recall rate.Specifically,recall rates of 0.915 and 0.82were obtained for Datasets 1 and 2,respectively.Although there was a slight decrease in accuracy,it aligned with the intended purpose of the search-and-secure software design.Experimental tests conducted within an accelerator tunnel demonstrated the effectiveness of this approach in achieving reliable recognition outcomes.
基金supported by the Medical Special Cultivation Project of Anhui University of Science and Technology(Grant No.YZ2023H2B013)the Anhui Provincial Key Research and Development Project(Grant No.2022i01020015)the Open Project of Key Laboratory of Conveyance Equipment(East China Jiaotong University),Ministry of Education(KLCE2022-01).
文摘The human pose paradigm is estimated using a transformer-based multi-branch multidimensional directed the three-dimensional(3D)method that takes into account self-occlusion,badly posedness,and a lack of depth data in the per-frame 3D posture estimation from two-dimensional(2D)mapping to 3D mapping.Firstly,by examining the relationship between the movements of different bones in the human body,four virtual skeletons are proposed to enhance the cyclic constraints of limb joints.Then,multiple parameters describing the skeleton are fused and projected into a high-dimensional space.Utilizing a multi-branch network,motion features between bones and overall motion features are extracted to mitigate the drift error in the estimation results.Furthermore,the estimated relative depth is projected into 3D space,and the error is calculated against real 3D data,forming a loss function along with the relative depth error.This article adopts the average joint pixel error as the primary performance metric.Compared to the benchmark approach,the estimation findings indicate an increase in average precision of 1.8 mm within the Human3.6M sample.
文摘This paper presents discrete wavelet transform （DWT） and its inverse （IDWT） with Haar wavelets as tools to compute the variable size interpolated versions of an image at optimum computational load. As a human observer moves closer to or farther from a scene, the retinal image of the scene zooms in or out, respectively. This zooming in or out can be modeled using variable scale interpolation. The paper proposes a novel way of applying DWT and IDWT in a piecewise manner by non-uniform down- or up-sampling of the images to achieve partially sampled versions of the images. The partially sampled versions are then aggregated to achieve the final variable scale interpolated images. The non-uniform down- or up-sampling here is a function of the required scale of interpolation. Appropriate zero padding is used to make the images suitable for the required non-uniform sampling and the subsequent interpolation to the required scale. The concept of zeroeth level DWT is introduced here, which works as the basis for interpolating the images to achieve bigger size than the original one. The main emphasis here is on the computation of variable size images at less computational load, without compromise of quality of images. The interpolated images to different sizes and the reconstructed images are benchmarked using the statistical parameters and visual comparison. It has been found that the proposed approach performs better as compared to bilinear and bicubic interpolation techniques.
基金supported by a grant form by the World Bank(FIo-016) for China capacity building for highly pathogenic avian influenza prevention and human pandemic influenza preparedness projectgranted by Australia, European Union,and other donor countries
文摘This article introduced the vision building concept about human influenza pandemic prevention and control.Different visions were built by creating different shapes of building blocks which also represented different organizations and physical facilities,respectively.The around-view reflection is required to be developed in the process of building so as to search for the ideal pattern.The correlation of all sectors and systems are established to combine different kinds of things,from one family to another,from communities,towns,counties,cities,rural areas, provinces to the state to handle trivial problems.These training objectives have been successfully accomplished,which has not only enriched the knowledge about prevention and control of influenza pandemic between different departments but also clarified the roles and responsibility. It lays the firm foundation for next cooperation between different departments,and make a bridge for the objective and choice of channel over human influenza pandemic prevention and control.
文摘Having proper sanitation and hygiene, access to affordable health care and enough food on the table are the basic conditions for a dignified life. This link between human dignity and the right to development was made very persuasively already in the White Paper on human rights, issued by the State Council of P.R.C. in 1991. The Declaration on the right to development can be considered the first successful joint action undertaken by Southern states in the area of human rights. The Declaration was based on Southern scholarship, such as the pioneering research conducted by the Senegalese jurist Kéba M’baye. And its adoption was the result of joint stage management performed by diplomats from different continents. Therefore the Declaration serves as a source of inspiration for the work of drafting a Comprehensive Southern Vision on human rights. The Vision document will lay out a common Southern outlook on human rights issues as an elaboration of the Universal Declaration.
文摘The aim of this paper is to create an interface for human-robot interaction.Specifically,musical performance parameters(i.e.vibrato expression)of the Waseda Flutist Robot No.4 Refined IV(WF-4RIV)are to be manipulated.This research focused on enabling the WF-4RIV to interact with human players(musicians)in a natural way.In this paper,as the first approach,a vision processing algorithm,which is able to track the 3D-orientation and position of a musical instrument,was developed.In particular,the robot acquires image data through two cameras attached to its head.Using color histogram matching and a particle filter,the position of the musician's hands on the instrument are tracked.Analysis of this data determines orientation and location of the instrument.These parameters are mapped to manipulate the musical expression of the WF-4RIV,more specifically sound vibrato and volume values.The authors present preliminary experiments to determine if the robot may dynamically change musical parameters while interacting with a human player(i.e.vibrato etc.).From the experimental results,they may confirm the feasibility of the interaction during the performance,although further research must be carried out to consider the physical constraints of the flutist robot.
基金supported by the National Natural Science Foundation of China and Microsoft Research Asia ( No.NSFC-61173096 No.61103140),NCET+3 种基金the Science and Technology Department of Zhejiang Province ( No.R1110679 No.2010R10006 No.2010C33095 No.Y1090592)
文摘This paper presents some human-inspired strategies for lighting control in a robot system for best scene interpretation,where the main intention is to avoid possible glares or highlights occurring in images. It firstly compares the characteristics of human eyes and robot eyes. Then some evaluation criteria are addressed to assess the lighting conditions. A bio-inspired method is adopted to avoid the visual glare which is caused by either direct illumination from large light sources or indirect illumination reflected by smooth surfaces. Appropriate methods are proposed to optimize the pose and optical parameters of the light source and the vision camera.
基金Projects(61262032,61173122)supported by the National Natural Science Foundation of ChinaProject(12JJ038)supported by the Key Project of Natural Science Foundation of Hunan Province,China+1 种基金Project(2012FJ3100)supported by the Hunan Provincial Science&Technology Department,ChinaProject(12B103)supported by the Youth Project of Hunan Universities and Colleges Science Research,China
文摘A shadow detection method using pulse couple neural network inspired by the characters of human visual system is proposed.More precisely,lateral inhibition of human vision and coefficient of variation are combined together to improve the pulse couple neural network.Shadow detection is considered to be a shadow region segmentation problem.Experiment shows that the presented method is consistent with human vision compared to shadow detection methods based on HSV and pulse couple neural network(PCNN) by both subjective and objective assessments.
基金supported and funded by KAU Scientific Endowment,King Abdulaziz University,Jeddah,Saudi Arabia.
文摘Human recognition technology based on biometrics has become a fundamental requirement in all aspects of life due to increased concerns about security and privacy issues.Therefore,biometric systems have emerged as a technology with the capability to identify or authenticate individuals based on their physiological and behavioral characteristics.Among different viable biometric modalities,the human ear structure can offer unique and valuable discriminative characteristics for human recognition systems.In recent years,most existing traditional ear recognition systems have been designed based on computer vision models and have achieved successful results.Nevertheless,such traditional models can be sensitive to several unconstrained environmental factors.As such,some traits may be difficult to extract automatically but can still be semantically perceived as soft biometrics.This research proposes a new group of semantic features to be used as soft ear biometrics,mainly inspired by conventional descriptive traits used naturally by humans when identifying or describing each other.Hence,the research study is focused on the fusion of the soft ear biometric traits with traditional(hard)ear biometric features to investigate their validity and efficacy in augmenting human identification performance.The proposed framework has two subsystems:first,a computer vision-based subsystem,extracting traditional(hard)ear biometric traits using principal component analysis(PCA)and local binary patterns(LBP),and second,a crowdsourcing-based subsystem,deriving semantic(soft)ear biometric traits.Several feature-level fusion experiments were conducted using the AMI database to evaluate the proposed algorithm’s performance.The obtained results for both identification and verification showed that the proposed soft ear biometric information significantly improved the recognition performance of traditional ear biometrics,reaching up to 12%for LBP and 5%for PCA descriptors;when fusing all three capacities PCA,LBP,and soft traits using k-nearest neighbors(KNN)classifier.
