We present a method for efficiently tracking objects represented as constellations of parts by integrating out the shape of the model. Parts-based models have been successfully applied to object recognition and tracking. However, the high dimensionality of such models present an obstacle to traditional particle filtering approaches. We can efficiently use parts-based models in a particle filter...

Single particle tracking is a powerful tool to investigate the function of biological molecules by following their motion in space. However, the simultaneous tracking of two different species of molecules is still difficult to realize without compromising the length or density of trajectories, the localization accuracy or the simplicity of the assay. Here, we demonstrate a simple dual color sin...

We present a comprehensive theory of closed-loop particle tracking for calculating the statistics of a diffusing fluorescent particle's motion relative to the tracking lock point. A detailed comparison is made between the theory and experimental results, with excellent quantitative agreement found in all cases. A generalization of the theory of (open-loop) fluorescence correlation spectroscopy ...

An object tracking method based on visual attention model and particle filter is presented. An improved visual attention model is employed to measure the similarity between tracked objects and candidate objects. Gaussian weighted color, intensity, orientation and motion saliency map are calculated with strategy to compose the attention value, which can be used to measure the similarity of the o...

In this paper, a novel method for tracking multiple soccer players based on a support vector machine (SVM) and a particle filter is proposed for a monocular fixed soccer video. This paper considers three main topics. First, the state of a particle filter presented in a 3D world coordinate space, instead of a 2D image coordinate space, provides a more realistic model tracking because depth consi...

Searching and tracking people in crowded urban areas where they can be occluded by static or dynamic obstacles is an important behavior for social robots which assist humans in urban outdoor environments. In this work, we propose a method that can handle in real-time searching and tracking people using a Highest Belief Particle Filter Searcher and Tracker. It makes use of a modified Particle Fi...

This paper deals with the task of tracking several similar looking athletes during a competition, using only a single camera. Due to the wide range of possible motions, non-rigid shape changes and mutual occlusions the tracking situations can become quite complex. We propose a novel method to use a high dimensional motion model for a particle filter without drastic increase in runtime. Integral...

In this paper, we proposed an object tracking method for video stream based on conventional particle filter. Feature vectors are extracted from coefficient matrices of Discrete Cosine Transform (DCT). The feature, as experiment showed, is very robust to occlusion and rotation and it is not sensitive to scale changes. The proposed method is efficient enough to be used in a real-time application....

In this chapter we present a new method for simulating the motion of a disperse particle phase in a carrier gas through porous media. We assume a sufficiently dilute particle-laden flow and compute, independently of the disperse phase, the steady laminar fluid velocity using the Immersed Boundary (IB) method. Given the velocity of the carrier gas, the equations of motion for the particles exper...

Particle tracking methods are a versatile computational technique central to the simulation of a wide range of scientiic applications. In this paper we present a new parallel approach for the dynamic partitioning of particle-mesh computational systems. The approach uses a framework, the \in-element" particle tracking method, based on the assumption that particle trajectories are computed by pro...