Real Time Parallel Implementation of Particles Filter Based Visual Tracking
نویسندگان
چکیده
Particle filtering is a widely used method to solve vision tracking problems. However, to be able to run in real-time on standard architecture, the state vector used in the particle filter must remain small [1]. We propose a parallel implementation of a 3D tracking algorithm operating on a stereo video stream and running in real-time on a cluster architecture. We demonstrate the efficiency of this implementation with a pedestrian tracking application.
منابع مشابه
An Efficient Target Tracking Algorithm Based on Particle Filter and Genetic Algorithm
In this paper, we propose an efficient hybrid Particle Filter (PF) algorithm for video tracking by employing a genetic algorithm to solve the sample impoverishment problem. In the presented method, the object to be tracked is selected by a rectangular window inside which a few numbers of particles are scattered. The particles’ weights are calculated based on the similarity between feature vecto...
متن کاملEffect of resampling steepness on particle filtering performance in visual tracking
This paper presents a proficiently developed resampling algorithm for particle filtering. In any filtering algorithm adopting the perception of particles, especially in visual tracking, resampling is an essential process that determines the algorithm’s performance and accuracy in the implementation step. It is usually a linear function of the weight of the particles, which determines the number...
متن کاملFixed-point FPGA Implementation of a Kalman Filter for Range and Velocity Estimation of Moving Targets
Tracking filters are extensively used within object tracking systems in order to provide consecutive smooth estimations of position and velocity of the object with minimum error. Namely, Kalman filter and its numerous variants are widely known as simple yet effective linear tracking filters in many diverse applications. In this paper, an effective method is proposed for designing and implementa...
متن کاملAn Optimization - Based Parallel Particle Filter for Multitarget Tracking
Particle filters are being used in a number of state estimation applications because of their capa bility to effectively solve nonlinear and non-Gaussian problems. However, they have high com putational requirements and this becomes even more so in the case of multitarget tracking, where data association is the bottleneck. In order to perform data association and estimation jointly, typically a...
متن کاملImplementation of the direction of arrival estimation algorithms by means of GPU-parallel processing in the Kuda environment (Research Article)
Direction-of-arrival (DOA) estimation of audio signals is critical in different areas, including electronic war, sonar, etc. The beamforming methods like Minimum Variance Distortionless Response (MVDR), Delay-and-Sum (DAS), and subspace-based Multiple Signal Classification (MUSIC) are the most known DOA estimation techniques. The mentioned methods have high computational complexity. Hence using...
متن کامل