Visual multiple‐object tracking for unknown clutter rate
نویسندگان
چکیده
منابع مشابه
Visual Multiple-Object Tracking for Unknown Clutter Rate
In most multi-object tracking algorithms, tuning of model parameters is of critical importance for reliable performance. In particular, we are interested in designing a robust tracking algorithm that is able to handle unknown false measurement rate. The proposed algorithm is based on coupling of two random finite set filters that share tracking parameters. Performance evaluation with visual sur...
متن کاملMulti-Target Tracking Based on Multi-Bernoulli Filter with Amplitude for Unknown Clutter Rate
Knowledge of the clutter rate is of critical importance in multi-target Bayesian tracking. However, estimating the clutter rate is a difficult problem in practice. In this paper, an improved multi-Bernoulli filter based on random finite sets for multi-target Bayesian tracking accommodating non-linear dynamic and measurement models, as well as unknown clutter rate, is proposed for radar sensors....
متن کاملClutter Mitigation for Target Tracking
Traditionally, the literature on target tracking assumes that the targets of interest are embedded in homogenous Rayleigh distributed background noise. It is most often assumed that purely kinematic point measurements are extracted from the sensor images, so that the tracking problem can be phrased in terms of data association. The tracker has to decide which point measurements are likely to ha...
متن کاملMulti-Bernoulli sensor-selection for multi-target tracking with unknown clutter and detection profiles
A new sensor-selection solution within a Multi-Bernoulli-based multi-target tracking framework is presented. The proposed method is especially designed for the general multi-target tracking case with no prior knowledge of the clutter distribution or the probability of detection, and uses a new task-driven objective function for this purpose. Step-by-step sequential Monte Carlo implementation of...
متن کاملClutter Removal in Sonar Image Target Tracking Using PHD Filter
In this paper we have presented a new procedure for sonar image target tracking using PHD filter besides K-means algorithm in high density clutter environment. We have presented K-means as data clustering technique in this paper to estimate the location of targets. Sonar images target tracking is a very good sample of high clutter environment. As can be seen, PHD filter because of its special f...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IET Computer Vision
سال: 2018
ISSN: 1751-9632,1751-9640
DOI: 10.1049/iet-cvi.2017.0600