Multi-Object Tracking with Correlation Filter for Autonomous Vehicle
نویسندگان
چکیده
منابع مشابه
Robust Vehicle Tracking Multi-feature Particle Filter
Object detection and tracking have been studied separately in most cases. Particle filtering has proven very successful for non-linear and nonGaussian estimation problems. This paper presents a new method for tracking moving vehicles with temporal disappearance. The proposed method can continue tracking after disappearance. Color distribution of objects is integrated into particle filtering alg...
متن کاملCFNN: Correlation Filter Neural Network for Visual Object Tracking
Albeit convolutional neural network (CNN) has shown promising capacity in many computer vision tasks, applying it to visual tracking is yet far from solved. Existing methods either employ a large external dataset to undertake exhaustive pre-training or suffer from less satisfactory results in terms of accuracy and robustness. To track single target in a wide range of videos, we present a novel ...
متن کاملIdentification of an Autonomous Underwater Vehicle Dynamic Using Extended Kalman Filter with ARMA Noise Model
In the procedure of designing an underwater vehicle or robot, its maneuverability and controllability must be simulated and tested, before the product is finalized for manufacturing. Since the hydrodynamic forces and moments highly affect the dynamic and maneuverability of the system, they must be estimated with a reasonable accuracy. In this study, hydrodynamic coefficients of an autonomous un...
متن کاملJoint Conditional Random Field Filter for Multi-Object Tracking
Object tracking can improve the performance of mobile robot especially in populated dynamic environments. A novel joint conditional random field Filter (JCRFF) based on conditional random field with hierarchical structure is proposed for multi‐object tracking by abstracting the data associations between objects and measurements to be a sequence of labels. Si...
متن کاملA Structural Correlation Filter Combined with A Multi-task Gaussian Particle Filter for Visual Tracking
In this paper, we propose a novel structural correlation filter combined with a multi-task Gaussian particle filter (KCF-GPF) model for robust visual tracking. We first present an assemble structure where several KCF trackers as weak experts provide a preliminary decision for a Gaussian particle filter to make a final decision. The proposed method is designed to exploit and complement the stren...
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: Sensors
سال: 2018
ISSN: 1424-8220
DOI: 10.3390/s18072004