This paper introduces an approach for visual tracking of multi-target with occlusion occurrence. Based on the author's previous work in which the Overlap Coefficient (OC) is used to detect the occlusion, in this p...This paper introduces an approach for visual tracking of multi-target with occlusion occurrence. Based on the author's previous work in which the Overlap Coefficient (OC) is used to detect the occlusion, in this paper a method of combining Bhattacharyya Coefficient (BC) and Kalman filter innovation term is proposed as the criteria for jointly detecting the occlusion occurrence. Fragmentation of target is introduced in order to closely monitor the occlusion development. In the course of occlusion, the Kalman predictor is applied to determine the location of the occluded target, and the criterion for checking the re-appearance of the occluded target is also presented. The proposed approach is put to test on a standard video sequence, suggesting the satisfactory performance in multi-target tracking.展开更多
Engineering tests can yield inaccurate data due to instrument errors,human factors,and environmental interference,introducing uncertainty in numerical model updating.This study employs the probability-box(p-box)method...Engineering tests can yield inaccurate data due to instrument errors,human factors,and environmental interference,introducing uncertainty in numerical model updating.This study employs the probability-box(p-box)method for representing observational uncertainty and develops a two-step approximate Bayesian computation(ABC)framework using time-series data.Within the ABC framework,Euclidean and Bhattacharyya distances are employed as uncertainty quantification metrics to delineate approximate likelihood functions in the initial and subsequent steps,respectively.A novel variational Bayesian Monte Carlo method is introduced to efficiently apply the ABC framework amidst observational uncertainty,resulting in rapid convergence and accurate parameter estimation with minimal iterations.The efficacy of the proposed updating strategy is validated by its application to a shear frame model excited by seismic wave and an aviation pump force sensor for thermal output analysis.The results affirm the efficiency,robustness,and practical applicability of the proposed method.展开更多
基金Supported by the Program for Technology Innovation Team of Ningbo Government (No. 2011B81002)the Ningbo University Science Research Foundation (No.xkl11075)
文摘This paper introduces an approach for visual tracking of multi-target with occlusion occurrence. Based on the author's previous work in which the Overlap Coefficient (OC) is used to detect the occlusion, in this paper a method of combining Bhattacharyya Coefficient (BC) and Kalman filter innovation term is proposed as the criteria for jointly detecting the occlusion occurrence. Fragmentation of target is introduced in order to closely monitor the occlusion development. In the course of occlusion, the Kalman predictor is applied to determine the location of the occluded target, and the criterion for checking the re-appearance of the occluded target is also presented. The proposed approach is put to test on a standard video sequence, suggesting the satisfactory performance in multi-target tracking.
基金supported by the National Natural Science Foundation of China(Grant No.U23B20105).
文摘Engineering tests can yield inaccurate data due to instrument errors,human factors,and environmental interference,introducing uncertainty in numerical model updating.This study employs the probability-box(p-box)method for representing observational uncertainty and develops a two-step approximate Bayesian computation(ABC)framework using time-series data.Within the ABC framework,Euclidean and Bhattacharyya distances are employed as uncertainty quantification metrics to delineate approximate likelihood functions in the initial and subsequent steps,respectively.A novel variational Bayesian Monte Carlo method is introduced to efficiently apply the ABC framework amidst observational uncertainty,resulting in rapid convergence and accurate parameter estimation with minimal iterations.The efficacy of the proposed updating strategy is validated by its application to a shear frame model excited by seismic wave and an aviation pump force sensor for thermal output analysis.The results affirm the efficiency,robustness,and practical applicability of the proposed method.
