In this paper, an improved implementation of multiple model Gaussian mixture probability hypothesis density （MM-GM-PHD） filter is proposed. For maneuvering target tracking, based on joint distribution, the existing ...In this paper, an improved implementation of multiple model Gaussian mixture probability hypothesis density （MM-GM-PHD） filter is proposed. For maneuvering target tracking, based on joint distribution, the existing MM-GM-PHD filter is relatively complex. To simplify the filter, model conditioned distribution and model probability are used in the improved MM-GM-PHD filter. In the algorithm, every Gaussian components describing existing, birth and spawned targets are estimated by multiple model method. The final results of the Gaussian components are the fusion of multiple model estimations. The algorithm does not need to compute the joint PHD distribution and has a simpler computation procedure. Compared with single model GM-PHD, the algorithm gives more accurate estimation on the number and state of the targets. Compared with the existing MM-GM-PHD algorithm, it saves computation time by more than 30%. Moreover, it also outperforms the interacting multiple model joint probabilistic data association （IMMJPDA） filter in a relatively dense clutter environment.展开更多
Object recognition and tracking are two of the most dynamic research sub-areas that belong to the field of Computer Vision.Computer vision is one of the most active research fields that lies at the intersection of dee...Object recognition and tracking are two of the most dynamic research sub-areas that belong to the field of Computer Vision.Computer vision is one of the most active research fields that lies at the intersection of deep learning and machine vision.This paper presents an efficient ensemble algorithm for the recognition and tracking of fixed shapemoving objects while accommodating the shift and scale invariances that the object may encounter.The first part uses the Maximum Average Correlation Height(MACH)filter for object recognition and determines the bounding box coordinates.In case the correlation based MACH filter fails,the algorithms switches to a much reliable but computationally complex feature based object recognition technique i.e.,affine scale invariant feature transform(ASIFT).ASIFT is used to accommodate object shift and scale object variations.ASIFT extracts certain features from the object of interest,providing invariance in up to six affine parameters,namely translation(two parameters),zoom,rotation and two camera axis orientations.However,in this paper,only the shift and scale invariances are used.The second part of the algorithm demonstrates the use of particle filters based Approximate Proximal Gradient(APG)technique to periodically update the coordinates of the object encapsulated in the bounding box.At the end,a comparison of the proposed algorithm with other stateof-the-art tracking algorithms has been presented,which demonstrates the effectiveness of the proposed algorithm with respect to the minimization of tracking errors.展开更多
This paper discusses the performance of a proposed panelized brick veneer over steel stud backup wall system and seismic isolation connections under lateral loads. The panelized wall system was developed to address so...This paper discusses the performance of a proposed panelized brick veneer over steel stud backup wall system and seismic isolation connections under lateral loads. The panelized wall system was developed to address some shortcomings of the conventional brick veneer wall type. The details of the system are briefly introduced. The study evaluated the performance of the system under out-of-plane simulated wind loads and in-plane cyclic loads using full-scale laboratory experiments. The test setup, test specimen, test procedure, and test results are presented and the performance of the system is evaluated accordingly.展开更多
The return to old building methods by mixing crop by-products with mineral binders is arousing great interest in Europe since about 25 years.The use of these bio-aggregates based materials for the design of building e...The return to old building methods by mixing crop by-products with mineral binders is arousing great interest in Europe since about 25 years.The use of these bio-aggregates based materials for the design of building envelopes is a valuable opportunity to deal with increasingly demanding thermal regulations.In addition,the regulatory framework is moving towards reducing the overall car-bon footprint of new buildings.Some traditional and historic buildings are based on timber framing with earth-straw as infill material for instance.Hemp concrete is a bio-based material that can be manually tamped in timber stud walls or more recently in the form of precast blocks.Owing to their low compressive strength,bio-based concretes using a large volume fraction of plant-derived aggregates are only considered as thermal and sound insulation materials.The structural design practice of wood frame walls does not assume any mechanical contribution of hemp concrete whereas it may contribute to the racking strength of the structure.In this context,more research is needed regarding the shear behavior of crop by-products and bio-based concretes.In this case,the objective of the study was to perform direct shear tests under three levels of normal pressure on hemp shiv and rice husk as unbound crop by-products.The results showed that the friction angle of the granular skeleton based on rice husk for a given relative displacement was significantly lower than that measured on hemp shiv.This is in accordance with what had been observed on bio-based concretes cast by mixing aggregates with lime and shear strength parameters measured by means of triaxial compression.展开更多
文摘In this paper, an improved implementation of multiple model Gaussian mixture probability hypothesis density （MM-GM-PHD） filter is proposed. For maneuvering target tracking, based on joint distribution, the existing MM-GM-PHD filter is relatively complex. To simplify the filter, model conditioned distribution and model probability are used in the improved MM-GM-PHD filter. In the algorithm, every Gaussian components describing existing, birth and spawned targets are estimated by multiple model method. The final results of the Gaussian components are the fusion of multiple model estimations. The algorithm does not need to compute the joint PHD distribution and has a simpler computation procedure. Compared with single model GM-PHD, the algorithm gives more accurate estimation on the number and state of the targets. Compared with the existing MM-GM-PHD algorithm, it saves computation time by more than 30%. Moreover, it also outperforms the interacting multiple model joint probabilistic data association （IMMJPDA） filter in a relatively dense clutter environment.
基金This research was supported by X-mind Corps program of National Research Foundation of Korea(NRF)funded by the Ministry of Science,ICT(No.2019H1D8A1105622)and the Soonchunhyang University Research Fund.
文摘Object recognition and tracking are two of the most dynamic research sub-areas that belong to the field of Computer Vision.Computer vision is one of the most active research fields that lies at the intersection of deep learning and machine vision.This paper presents an efficient ensemble algorithm for the recognition and tracking of fixed shapemoving objects while accommodating the shift and scale invariances that the object may encounter.The first part uses the Maximum Average Correlation Height(MACH)filter for object recognition and determines the bounding box coordinates.In case the correlation based MACH filter fails,the algorithms switches to a much reliable but computationally complex feature based object recognition technique i.e.,affine scale invariant feature transform(ASIFT).ASIFT is used to accommodate object shift and scale object variations.ASIFT extracts certain features from the object of interest,providing invariance in up to six affine parameters,namely translation(two parameters),zoom,rotation and two camera axis orientations.However,in this paper,only the shift and scale invariances are used.The second part of the algorithm demonstrates the use of particle filters based Approximate Proximal Gradient(APG)technique to periodically update the coordinates of the object encapsulated in the bounding box.At the end,a comparison of the proposed algorithm with other stateof-the-art tracking algorithms has been presented,which demonstrates the effectiveness of the proposed algorithm with respect to the minimization of tracking errors.
文摘This paper discusses the performance of a proposed panelized brick veneer over steel stud backup wall system and seismic isolation connections under lateral loads. The panelized wall system was developed to address some shortcomings of the conventional brick veneer wall type. The details of the system are briefly introduced. The study evaluated the performance of the system under out-of-plane simulated wind loads and in-plane cyclic loads using full-scale laboratory experiments. The test setup, test specimen, test procedure, and test results are presented and the performance of the system is evaluated accordingly.
文摘The return to old building methods by mixing crop by-products with mineral binders is arousing great interest in Europe since about 25 years.The use of these bio-aggregates based materials for the design of building envelopes is a valuable opportunity to deal with increasingly demanding thermal regulations.In addition,the regulatory framework is moving towards reducing the overall car-bon footprint of new buildings.Some traditional and historic buildings are based on timber framing with earth-straw as infill material for instance.Hemp concrete is a bio-based material that can be manually tamped in timber stud walls or more recently in the form of precast blocks.Owing to their low compressive strength,bio-based concretes using a large volume fraction of plant-derived aggregates are only considered as thermal and sound insulation materials.The structural design practice of wood frame walls does not assume any mechanical contribution of hemp concrete whereas it may contribute to the racking strength of the structure.In this context,more research is needed regarding the shear behavior of crop by-products and bio-based concretes.In this case,the objective of the study was to perform direct shear tests under three levels of normal pressure on hemp shiv and rice husk as unbound crop by-products.The results showed that the friction angle of the granular skeleton based on rice husk for a given relative displacement was significantly lower than that measured on hemp shiv.This is in accordance with what had been observed on bio-based concretes cast by mixing aggregates with lime and shear strength parameters measured by means of triaxial compression.
