Mohammad Javad Parseh | University of Tabriz (original) (raw)
Supervisors: Dr. Mir Hadi Seyedarabi
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Papers by Mohammad Javad Parseh
http://ieeexplore.ieee.org, Oct 18, 2012
In this paper, a new approach is proposed for tracking maneuvering target by improving the basic ... more In this paper, a new approach is proposed for tracking maneuvering target by improving the basic SIR algorithm. We proposed a dynamic model for maneuvering target. If changes of target model are larger than a predetermined threshold, then the target model will be updated. Practical results show that our proposed approach considerably improves accurate tracking of a maneuvering object. We will compare our proposed approach with the basic SIR algorithm in tracking a single maneuvering aircraft.
Results of our proposed algorithm are also illustrated in tracking different maneuvering targets on few real-world case study videos.
In this paper, we applied a dynamic model for manoeuvring targets in SIR particle filter algorith... more In this paper, we applied a dynamic model for manoeuvring targets in SIR particle filter algorithm for improving tracking accuracy of multiple manoeuvring targets. In our proposed approach, a color distribution model is used to detect changes of target's model . Our proposed approach controls deformation of target's model. If deformation of target's model is larger than a predetermined threshold, then the model will be updated. Global Nearest Neighbor (GNN) algorithm is used as data association algorithm. We named our proposed method as Deformation Detection Particle Filter (DDPF) . DDPF approach is compared with basic SIR-PF algorithm on real airshow videos. Comparisons results show that, the basic SIR-PF algorithm is not able to track the manoeuvring targets when the rotation or scaling is occurred in target' s model. However, DDPF approach updates target's model when the rotation or scaling is occurred. Thus, the proposed approach is able to track the manoeuvring targets more efficiently and accurately.
http://ieeexplore.ieee.org, Oct 18, 2012
In this paper, a new approach is proposed for tracking maneuvering target by improving the basic ... more In this paper, a new approach is proposed for tracking maneuvering target by improving the basic SIR algorithm. We proposed a dynamic model for maneuvering target. If changes of target model are larger than a predetermined threshold, then the target model will be updated. Practical results show that our proposed approach considerably improves accurate tracking of a maneuvering object. We will compare our proposed approach with the basic SIR algorithm in tracking a single maneuvering aircraft.
Results of our proposed algorithm are also illustrated in tracking different maneuvering targets on few real-world case study videos.
In this paper, we applied a dynamic model for manoeuvring targets in SIR particle filter algorith... more In this paper, we applied a dynamic model for manoeuvring targets in SIR particle filter algorithm for improving tracking accuracy of multiple manoeuvring targets. In our proposed approach, a color distribution model is used to detect changes of target's model . Our proposed approach controls deformation of target's model. If deformation of target's model is larger than a predetermined threshold, then the model will be updated. Global Nearest Neighbor (GNN) algorithm is used as data association algorithm. We named our proposed method as Deformation Detection Particle Filter (DDPF) . DDPF approach is compared with basic SIR-PF algorithm on real airshow videos. Comparisons results show that, the basic SIR-PF algorithm is not able to track the manoeuvring targets when the rotation or scaling is occurred in target' s model. However, DDPF approach updates target's model when the rotation or scaling is occurred. Thus, the proposed approach is able to track the manoeuvring targets more efficiently and accurately.