In this article, we focus to study about modified objective function approach for multiobjective optimization problem with vanishing constraints. An equivalent η-approximated multiobjective optimization problem is co...In this article, we focus to study about modified objective function approach for multiobjective optimization problem with vanishing constraints. An equivalent η-approximated multiobjective optimization problem is constructed by a modification of the objective function in the original considered optimization problem. Furthermore, we discuss saddle point criteria for the aforesaid problem. Moreover, we present some examples to verify the established results.展开更多
The rapid development of image processing techniques has made it extremely easy to alter the content of images or create newimages.So photographs,which appear in magazines,social media,and political attacks,can no lon...The rapid development of image processing techniques has made it extremely easy to alter the content of images or create newimages.So photographs,which appear in magazines,social media,and political attacks,can no longer be trusted.A novel and effective technique is proposed in this paper to expose image forgery using inconsistent reflection vanishing point(RVP).More specifically,the definition of error distance is given,sin^2()-based function is proposed to normalize error distance,and a reasonable threshold value is set to detect image forgery.The experimental data and results are presented to demonstrate the accuracy and effectiveness of the technique.展开更多
The vanishing point detection technology helps automatic driving. In this paper, the straight lines on the road associated with the vanishing point are extracted efficiently by using the regional division and angle li...The vanishing point detection technology helps automatic driving. In this paper, the straight lines on the road associated with the vanishing point are extracted efficiently by using the regional division and angle limitation. And, the vanishing point is detected robustly by using the fast M-estimation method. Proposed method could detect straight-line features associated with vanishing point detection efficient on the road. And the vanishing point was detected exactly by the effect of the fast M-estimation method when the straight-line features not associated with vanishing point detection were detected. The processing time of the proposed method was faster than the camera flame rate （30 fps）. Thus, the proposed method is capable of real-time processing.展开更多
Reading culture in many African societies is on a downward spiral READING culture varies in a number of ways across African societies,but what is generally perceived about Africans is that they are not noted for frequ...Reading culture in many African societies is on a downward spiral READING culture varies in a number of ways across African societies,but what is generally perceived about Africans is that they are not noted for frequently reading books,magazines,newspapers or any literary materials-even in their leisure time. This is summed up in a popular adage,which says that whenever you want to hide something from an African,you should just write it in a book. But is this perception really true that Africans are people who lack a good reading culture?展开更多
3D object detection is one of the most challenging research tasks in computer vision. In order to solve the problem of template information dependency of 3D object proposal in the method of 3D object detection based o...3D object detection is one of the most challenging research tasks in computer vision. In order to solve the problem of template information dependency of 3D object proposal in the method of 3D object detection based on 2.5D information, we proposed a 3D object detector based on fusion of vanishing point and prior orientation, which estimates an accurate 3D proposal from 2.5D data, and provides an excellent start point for 3D object classification and localization. The algorithm first calculates three mutually orthogonal vanishing points by the Euler angle principle and projects them into the pixel coordinate system. Then, the top edge of the 2D proposal is sampled by the preset sampling pitch, and the first one vertex is taken. Finally, the remaining seven vertices of the 3D proposal are calculated according to the linear relationship between the three vanishing points and the vertices, and the complete information of the 3D proposal is obtained. The experimental results show that this proposed method improves the Mean Average Precision score by 2.7% based on the Amodal3Det method.展开更多
this paper,we propose a class of smoothing-regularization methods for solving the mathematical programming with vanishing constraints.These methods include the smoothing-regularization method proposed by Kanzow et al....this paper,we propose a class of smoothing-regularization methods for solving the mathematical programming with vanishing constraints.These methods include the smoothing-regularization method proposed by Kanzow et al.in[Comput.Optim.Appl.,2013,55(3):733-767]as a special case.Under the weaker conditions than the ones that have been used by Kanzow et al.in 2013,we prove that the Mangasarian-Fromovitz constraint qualification holds at the feasible points of smoothing-regularization problem.We also analyze that the convergence behavior of the proposed smoothing-regularization method under mild conditions,i.e.,any accumulation point of the stationary point sequence for the smoothing-regularization problem is a strong stationary point.Finally,numerical experiments are given to show the efficiency of the proposed methods.展开更多
Advanced deep learning technology has made great progress in generic object detection of autonomous driving,yet it is still challenging to detect small road hazards in a long distance owing to lack of large-scale smal...Advanced deep learning technology has made great progress in generic object detection of autonomous driving,yet it is still challenging to detect small road hazards in a long distance owing to lack of large-scale small-object datasets and dedicated methods.This work addresses the challenge from two aspects.Firstly,a self-collected long-distance road object dataset(TJ-LDRO)is introduced,which consists of 109,337 images and is the largest dataset so far for the small road object detection research.Secondly,a vanishing-point-guided context-aware network(VCANet)is proposed,which utilizes the vanishing point prediction block and the context-aware center detection block to obtain semantic information.The multi-scale feature fusion pipeline and the upsampling block in VCANet are introduced to enhance the region of interest(ROI)feature.The experimental results with TJ-LDRO dataset show that the proposed method achieves better performance than the representative generic object detection methods.This work fills a critical capability gap in small road hazards detection for high-speed autonomous vehicles.展开更多
基金financially supported by the CSIR,New Delhi,India through Grant no.:25(0266)/17/EMR-II
文摘In this article, we focus to study about modified objective function approach for multiobjective optimization problem with vanishing constraints. An equivalent η-approximated multiobjective optimization problem is constructed by a modification of the objective function in the original considered optimization problem. Furthermore, we discuss saddle point criteria for the aforesaid problem. Moreover, we present some examples to verify the established results.
基金Fundamental Research Funds for the Central Universities,China(No.2232015D3-25)
文摘The rapid development of image processing techniques has made it extremely easy to alter the content of images or create newimages.So photographs,which appear in magazines,social media,and political attacks,can no longer be trusted.A novel and effective technique is proposed in this paper to expose image forgery using inconsistent reflection vanishing point(RVP).More specifically,the definition of error distance is given,sin^2()-based function is proposed to normalize error distance,and a reasonable threshold value is set to detect image forgery.The experimental data and results are presented to demonstrate the accuracy and effectiveness of the technique.
文摘The vanishing point detection technology helps automatic driving. In this paper, the straight lines on the road associated with the vanishing point are extracted efficiently by using the regional division and angle limitation. And, the vanishing point is detected robustly by using the fast M-estimation method. Proposed method could detect straight-line features associated with vanishing point detection efficient on the road. And the vanishing point was detected exactly by the effect of the fast M-estimation method when the straight-line features not associated with vanishing point detection were detected. The processing time of the proposed method was faster than the camera flame rate （30 fps）. Thus, the proposed method is capable of real-time processing.
文摘Reading culture in many African societies is on a downward spiral READING culture varies in a number of ways across African societies,but what is generally perceived about Africans is that they are not noted for frequently reading books,magazines,newspapers or any literary materials-even in their leisure time. This is summed up in a popular adage,which says that whenever you want to hide something from an African,you should just write it in a book. But is this perception really true that Africans are people who lack a good reading culture?
基金Supported by the National Natural Science Foundation of China(61772328,61802253,61831018)
文摘3D object detection is one of the most challenging research tasks in computer vision. In order to solve the problem of template information dependency of 3D object proposal in the method of 3D object detection based on 2.5D information, we proposed a 3D object detector based on fusion of vanishing point and prior orientation, which estimates an accurate 3D proposal from 2.5D data, and provides an excellent start point for 3D object classification and localization. The algorithm first calculates three mutually orthogonal vanishing points by the Euler angle principle and projects them into the pixel coordinate system. Then, the top edge of the 2D proposal is sampled by the preset sampling pitch, and the first one vertex is taken. Finally, the remaining seven vertices of the 3D proposal are calculated according to the linear relationship between the three vanishing points and the vertices, and the complete information of the 3D proposal is obtained. The experimental results show that this proposed method improves the Mean Average Precision score by 2.7% based on the Amodal3Det method.
基金Supported in part by NSFC(No.11961011)Guangxi Science and Technology Base and Talents Special Project(No.2021AC06001).
文摘this paper,we propose a class of smoothing-regularization methods for solving the mathematical programming with vanishing constraints.These methods include the smoothing-regularization method proposed by Kanzow et al.in[Comput.Optim.Appl.,2013,55(3):733-767]as a special case.Under the weaker conditions than the ones that have been used by Kanzow et al.in 2013,we prove that the Mangasarian-Fromovitz constraint qualification holds at the feasible points of smoothing-regularization problem.We also analyze that the convergence behavior of the proposed smoothing-regularization method under mild conditions,i.e.,any accumulation point of the stationary point sequence for the smoothing-regularization problem is a strong stationary point.Finally,numerical experiments are given to show the efficiency of the proposed methods.
基金This research has received funding from the National Natural Science Foundation of China(No.61906138)National Key Research and Development Program of China(No.2016YFB0100901)Shanghai AI Innovative Development Project 2018,and Shanghai Rising Star Program(No.21QC1400900).
文摘Advanced deep learning technology has made great progress in generic object detection of autonomous driving,yet it is still challenging to detect small road hazards in a long distance owing to lack of large-scale small-object datasets and dedicated methods.This work addresses the challenge from two aspects.Firstly,a self-collected long-distance road object dataset(TJ-LDRO)is introduced,which consists of 109,337 images and is the largest dataset so far for the small road object detection research.Secondly,a vanishing-point-guided context-aware network(VCANet)is proposed,which utilizes the vanishing point prediction block and the context-aware center detection block to obtain semantic information.The multi-scale feature fusion pipeline and the upsampling block in VCANet are introduced to enhance the region of interest(ROI)feature.The experimental results with TJ-LDRO dataset show that the proposed method achieves better performance than the representative generic object detection methods.This work fills a critical capability gap in small road hazards detection for high-speed autonomous vehicles.
