Tracking deforming objects involves estimating the global motion of the object and its local deformations as functions of time. Tracking algorithms using Kalman filters or particle filters have been proposed for tracking such objects, but these have limitations due to the lack of dynamic shape information. In this paper, we propose a novel method based on employing a locally linear embedding in...

Aimed to problem that particles exist degradation in particle filter (PF) algorithm for target tracking which is used in Wireless Sensor Networks, a new particle filter target tracking algorithm (GPF) based on genetic algorithm was proposed in this paper. First, based on the description of the PF algorithm, the factors that affect the degradation were analyzed, which were importance function an...

For high dynamic applications of GNSS receivers, the tracking sensitivity is heavily affected by the large unpredictable motion dynamics. The stability of the traditional tracking approaches is poor when outlier occurs among observations. In this paper, a novel Gaussian Particle Filtering-based carrier tracking algorithm is proposed for high dynamic GNSS signals. The proposed algorithm can work...

In this paper, we propose a novel algorithm for articulated object tracking, based on a hierarchical search and particle swarm optimization. Our approach aims to reduce the complexity induced by the high dimensional state space in articulated object tracking by decomposing the search space into subspaces and then using particle swarms to optimize over these subspaces hierarchically. Moreover, t...

In an optical tweezers system, the force measurement with a resolution less than pico-Newton can be achieved by precise measurement and analysis of the trapped particle trajectory. Typically, this single particle tracking technique is realized by a quadrant position sensor which detects the scattering lights of the trapping laser beam from the trapped particle. However, as the radius of the tra...

Human tracking is the process of locating moving objects (human) over time using camera. It has wide number of applications like security and surveillance, traffic control, video editing, medical imaging etc. It can be a time consuming process due to the large amount of data contained in video. The objective of human tracking is to associate target objects in consecutive video frames. To initia...

This paper addresses the application of sequential importance sampling (SIS) schemes to tracking DOAs of an unknown number of sources, using a passive array of sensors. This proposed technique has signi cant advantages in this application, including the ability to detect a changing number of signals at arbitrary times throughout the observation period, and that the requirement for quasi-station...

Particle filtering is a sequential Monte Carlo technique that recursively computes the posterior probability density function using the concept of “Importance Sampling”. This paper considers the application of particle filtering technique to a target tracking application, in which a radar sends a signal towards a target and estimates the state (position and velocity) of the target using the obs...