Discriminative correlation filters(DCF)are efficient in visual tracking and have advanced the field significantly.However,the symmetry of correlation(or convolution)operator results in computational problems and does ...Discriminative correlation filters(DCF)are efficient in visual tracking and have advanced the field significantly.However,the symmetry of correlation(or convolution)operator results in computational problems and does harm to the generalized translation equivariance.The former problem has been approached in many ways,whereas the latter one has not been well recognized.In this paper,we analyze the problems with the symmetry of circular convolution and propose an asymmetric one,which as a generalization of the former has a weak generalized translation equivariance property.With this operator,we propose a tracker called the asymmetric discriminative correlation filter(ADCF),which is more sensitive to translations of targets.Its asymmetry allows the filter and the samples to have different sizes.This flexibility makes the computational complexity of ADCF more controllable in the sense that the number of filter parameters will not grow with the sample size.Moreover,the normal matrix of ADCF is a block matrix with each block being a two-level block Toeplitz matrix.With this well-structured normal matrix,we design an algorithm for multiplying an N×N two-level block Toeplitz matrix by a vector with time complexity O(N log N)and space complexity O(N),instead of O(N^2).Unlike DCF-based trackers,introducing spatial or temporal regularization does not increase the essential computational complexity of ADCF.Comparative experiments are performed on a synthetic dataset and four benchmarks,including OTB-2013,OTB-2015,VOT-2016,and Temple-Color,and the results show that our method achieves state-of-the-art visual tracking performance.展开更多
A robust and eficient feature matching method is necessary for visual navigation in asteroid-landing missions.Based on the visual navigation framework and motion characteristics of asteroids,a robust and efficient tem...A robust and eficient feature matching method is necessary for visual navigation in asteroid-landing missions.Based on the visual navigation framework and motion characteristics of asteroids,a robust and efficient template feature matching method is proposed to adapt to feature distortion and scale change cases for visual navigation of asteroids.The proposed method is primarily based on a motion-constrained discriminative correlation filter(DCF).The prior information provided by the motion constraints between sequence images is used to provide a predicted search region for template feature matching.Additionally,some specific template feature samples are generated using the motion constraints for correlation filter learning,which is beneficial for training a scale and feature distortion adaptive correlation filter for accurate feature matching.Moreover,average peak-to-correlation energy(APCE)and jointly consistent measurements(JCMs)were used to eliminate false matching.Images captured by the Touch And Go Camera System(TAGCAMS)of the Bennu asteroid were used to evaluate the performance of the proposed method.In particular,both the robustness and accuracy of region matching and template center matching are evaluated.The qualitative and quantitative results illustrate the advancement of the proposed method in adapting to feature distortions and large-scale changes during spacecraft landing.展开更多
Energy resolution is affected by the intrinsic energy resolution of the detector, ballistic deficit, pileup pulses and noise. Pile-up pulses become the dominant factor that degrades energy resolution after the system ...Energy resolution is affected by the intrinsic energy resolution of the detector, ballistic deficit, pileup pulses and noise. Pile-up pulses become the dominant factor that degrades energy resolution after the system is established, so pile-up rejection is often applied to obtain good energy resolution by discarding pulses that are expected to be contaminated by pile-up. However, pile-up rejection can reduce count rates and thus lower the measurement precision. In order to improve count rates and maintain energy resolution, a new method of pile-up pulse identification based on trapezoidal pulse shaping is presented. Combined with pulse width discrimination, this method is implemented by recording pulses that are not seriously piled up. Some experimental tests with a Cu-Pb alloy sample are carried out to verify the performance of this method in X-ray spectrometry. The results show that the method can significantly improve count rates without degrading energy resolution.展开更多
基金Project supported by the National Natural Science Foundation of China(No.61773270)the Key Research and Development Project of Sichuan Province,China(No.2019YFG0491)。
文摘Discriminative correlation filters(DCF)are efficient in visual tracking and have advanced the field significantly.However,the symmetry of correlation(or convolution)operator results in computational problems and does harm to the generalized translation equivariance.The former problem has been approached in many ways,whereas the latter one has not been well recognized.In this paper,we analyze the problems with the symmetry of circular convolution and propose an asymmetric one,which as a generalization of the former has a weak generalized translation equivariance property.With this operator,we propose a tracker called the asymmetric discriminative correlation filter(ADCF),which is more sensitive to translations of targets.Its asymmetry allows the filter and the samples to have different sizes.This flexibility makes the computational complexity of ADCF more controllable in the sense that the number of filter parameters will not grow with the sample size.Moreover,the normal matrix of ADCF is a block matrix with each block being a two-level block Toeplitz matrix.With this well-structured normal matrix,we design an algorithm for multiplying an N×N two-level block Toeplitz matrix by a vector with time complexity O(N log N)and space complexity O(N),instead of O(N^2).Unlike DCF-based trackers,introducing spatial or temporal regularization does not increase the essential computational complexity of ADCF.Comparative experiments are performed on a synthetic dataset and four benchmarks,including OTB-2013,OTB-2015,VOT-2016,and Temple-Color,and the results show that our method achieves state-of-the-art visual tracking performance.
基金funded by the National Natural Science Foundation of China under Grant Nos.41822106 and 42101447the Dawn Scholar of Shanghai Program under Grant No.18SG22+2 种基金the Science and Technology on Aerospace Flight Dynamics Laboratory,China,under Grant No.KGJ6142210110305State Key Laboratory of Disaster Reduction in Civil Engineering under Grant No.SLDRCE19-B-35Fundamental Research Funds for the Central Universities of China.
文摘A robust and eficient feature matching method is necessary for visual navigation in asteroid-landing missions.Based on the visual navigation framework and motion characteristics of asteroids,a robust and efficient template feature matching method is proposed to adapt to feature distortion and scale change cases for visual navigation of asteroids.The proposed method is primarily based on a motion-constrained discriminative correlation filter(DCF).The prior information provided by the motion constraints between sequence images is used to provide a predicted search region for template feature matching.Additionally,some specific template feature samples are generated using the motion constraints for correlation filter learning,which is beneficial for training a scale and feature distortion adaptive correlation filter for accurate feature matching.Moreover,average peak-to-correlation energy(APCE)and jointly consistent measurements(JCMs)were used to eliminate false matching.Images captured by the Touch And Go Camera System(TAGCAMS)of the Bennu asteroid were used to evaluate the performance of the proposed method.In particular,both the robustness and accuracy of region matching and template center matching are evaluated.The qualitative and quantitative results illustrate the advancement of the proposed method in adapting to feature distortions and large-scale changes during spacecraft landing.
基金Supported by National Natural Science Foundation of China(11475036,41404108)
文摘Energy resolution is affected by the intrinsic energy resolution of the detector, ballistic deficit, pileup pulses and noise. Pile-up pulses become the dominant factor that degrades energy resolution after the system is established, so pile-up rejection is often applied to obtain good energy resolution by discarding pulses that are expected to be contaminated by pile-up. However, pile-up rejection can reduce count rates and thus lower the measurement precision. In order to improve count rates and maintain energy resolution, a new method of pile-up pulse identification based on trapezoidal pulse shaping is presented. Combined with pulse width discrimination, this method is implemented by recording pulses that are not seriously piled up. Some experimental tests with a Cu-Pb alloy sample are carried out to verify the performance of this method in X-ray spectrometry. The results show that the method can significantly improve count rates without degrading energy resolution.
