Xiaopin Zhong

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Multiple-target tracking in video (MTTV) presents a technical challenge in video surveillance applications. In this paper, we formulate the MTTV problem using dynamic Markov network (DMN) techniques. Our model consists of three coupled Markov random fields: 1) a field for the joint state of the multitarget; 2) a binary random process for the existence of(More)
To achieve robust system, more and more vision researchers take into account fusing multiple visual cues. In this paper, we propose a novel strategy to integrate multiple naive cues for head tracking. Firstly, a cue dependency model is constructed via graphical model. Secondly, a new inference procedure based on non-parametric belief propagation is built(More)
Rather than the difficulties of highly non-linear and non-Gaussian observation process and the state distribution in single target tracking, the presence of a large, varying number of targets and their interactions place more challenge on visual tracking. To overcome these difficulties, we formulate multiple targets tracking problem in a dynamic Markov(More)
We propose a sequential Monte Carlo data association algorithm based on a two-level computational framework for tracking varying number of interacting objects in dynamic scene. Firstly, we propose a hybrid measurements generation process to facilitate varying number problems, the process mixes target-oriented measurements provided by target dynamics prior(More)
In order to inspect the visual defects of polymer polarizer, an off-line automatic optical system (AOI) is proposed in this paper. It employs a plane CCD camera to capture the image of polarizer, and the Vision-Development-Module (VDM) © to process and analyze the image. Simple algorithm to determine the key parameters, such as the range of gray(More)
This paper presents a robust player tracking method for sports video analysis. In order to track agile player stably and robustly, we employ multiple models method, with a mean shift procedure corresponding to each model for player localization. Furthermore, we define pseudo measurement via fusing the measurements obtained by mean shift procedure. And the(More)
Bayesian networks (BNs) is widely used for system reliability modeling because of its versatility. It is crucial to build BNs from reliability data without experts' intervene. However, the BNs structure learning is still an open problem. Traditional approaches always integrate a structure scoring metric with a particular heuristically searching method. This(More)
In this paper, a new active control framework is developed for non-LTI continuous-time system, which is closer to the real world. Like other control system developments, it consists of two major parts: observer design and controller design. For the observer, the dynamic system is modelled as a jump Markov linear system whose parameters evolve along with the(More)