93 citations · 288 across the 36 of their papers we have counts for
37 papers
Variational PMB filter via coordinate descent Kullback-Leibler divergence minimisation
Ángel F. García-Fernández, Yuxuan Xia
This paper presents a new derivation of the variational Poisson multi-Bernoulli (V-PMB) filter for multi-target estimation proposed in [#Williams15]. The proposed derivation is bas…
An Extended Object Poisson Multi-Bernoulli Filter with Zero-Inflated Poisson Measurement Model Using Belief Propagation
Xueqi Qiu, Yuxuan Xia, Hyowon Kim +1
This paper presents an efficient implementation of the extended object Poisson multi-Bernoulli (PMB) filter under the zero-inflated Poisson (ZIP) object measurement model using par…
Efficient Implementations of Extended Object PMBM Filters with Blocked Gibbs Sampling
Yuxuan Xia, Ángel F. García-Fernández, Lennart Svensson
This paper considers multiple extended object tracking based on Poisson multi-Bernoulli mixture (PMBM) filtering, which gives the closed-form Bayesian solution for standard multipl…
Event-Triggered Distributed Target Tracking via PRIMEX
Yuxuan Xia, Kuo-Chu Chang, Xueqi Qiu +3
PRIMEX (prime-based graph encoding and extraction) is a recently proposed framework for scalable distributed fusion. In PRIMEX, the information pedigree of state estimates or proba…
Occlusion-Aware Multi-Object Tracking via Expected Probability of Detection
Jan Krejčí, Oliver Kost, Yuxuan Xia +2
This paper addresses multi-object systems, where objects may occlude one another relative to the sensor. The standard point-object model for detection-based sensors is enhanced so…
Model-based Multi-object Visual Tracking: Identification and Standard Model Limitations
Jan Krejčí, Oliver Kost, Yuxuan Xia +2
This paper uses multi-object tracking methods known from the radar tracking community to address the problem of pedestrian tracking using 2D bounding box detections. The standard p…
GOSPA and T-GOSPA quasi-metrics for evaluation of multi-object tracking algorithms
Ángel F. García-Fernández, Jinhao Gu, Lennart Svensson +4
This paper introduces two quasi-metrics for performance assessment of multi-object tracking (MOT) algorithms. One quasi-metric is an extension of the generalised optimal subpattern…
Probabilistic Trajectory GOSPA: A Metric for Uncertainty-Aware Multi-Object Tracking Performance Evaluation
Yuxuan Xia, Ángel F. García-Fernández, Johan Karlsson +3
This paper presents a generalization of the trajectory general optimal sub-pattern assignment (GOSPA) metric for evaluating multi-object tracking algorithms that provide trajectory…
Probabilistic GOSPA: A Metric for Performance Evaluation of Multi-Object Filters with Uncertainties
Yuxuan Xia, Ángel F. García-Fernández, Johan Karlsson +3
This paper presents a probabilistic generalization of the Generalized Optimal Sub-Pattern Assignment (GOSPA) metric, termed P-GOSPA. The GOSPA metric has been widely used to evalua…
TGOSPA Metric Parameters Selection and Evaluation for Visual Multi-object Tracking
Jan Krejčí, Oliver Kost, Ondřej Straka +3
Multi-object tracking algorithms are deployed in various applications, each with different performance requirements. For example, track switches pose significant challenges for off…
Target Handover in Distributed Integrated Sensing and Communication
Yu Ge, Ossi Kaltiokallio, Hui Chen +7
The concept of 6G distributed integrated sensing and communications (DISAC) builds upon the functionality of integrated sensing and communications (ISAC) by integrating distributed…
Hybrid PHD-PMB Trajectory Smoothing Using Backward Simulation
Yuxuan Xia, Ángel F. García-Fernández, Lennart Svensson
The probability hypothesis density (PHD) and Poisson multi-Bernoulli (PMB) filters are two popular set-type multi-object filters. Motivated by the fact that the multi-object filter…
Batch SLAM with PMBM Data Association Sampling and Graph-Based Optimization
Yu Ge, Ossi Kaltiokallio, Yuxuan Xia +6
Simultaneous localization and mapping (SLAM) methods need to both solve the data association (DA) problem and the joint estimation of the sensor trajectory and the map, conditioned…
Transformer-Based Multi-Object Smoothing with Decoupled Data Association and Smoothing
Juliano Pinto, Georg Hess, Yuxuan Xia +2
Multi-object tracking (MOT) is the task of estimating the state trajectories of an unknown and time-varying number of objects over a certain time window. Several algorithms have be…
Markov Chain Monte Carlo Multi-Scan Data Association for Sets of Trajectories
Yuxuan Xia, Ángel F. García-Fernández, Lennart Svensson
This paper considers a batch solution to the multi-object tracking problem based on sets of trajectories. Specifically, we present two offline implementations of the trajectory Poi…
Which Framework is Suitable for Online 3D Multi-Object Tracking for Autonomous Driving with Automotive 4D Imaging Radar?
Jianan Liu, Guanhua Ding, Yuxuan Xia +4
Online 3D multi-object tracking (MOT) has recently received significant research interests due to the expanding demand of 3D perception in advanced driver assistance systems (ADAS)…
LEGO: Learning and Graph-Optimized Modular Tracker for Online Multi-Object Tracking with Point Clouds
Zhenrong Zhang, Jianan Liu, Yuxuan Xia +3
Online multi-object tracking (MOT) plays a pivotal role in autonomous systems. The state-of-the-art approaches usually employ a tracking-by-detection method, and data association p…
Set-Type Belief Propagation with Applications to Poisson Multi-Bernoulli SLAM
Hyowon Kim, Angel F. García-Fernández, Yu Ge +3
Belief propagation (BP) is a useful probabilistic inference algorithm for efficiently computing approximate marginal probability densities of random variables. However, in its stan…
Poisson multi-Bernoulli mixture filter with general target-generated measurements and arbitrary clutter
Ángel F. García-Fernández, Yuxuan Xia, Lennart Svensson
This paper shows that the Poisson multi-Bernoulli mixture (PMBM) density is a multi-target conjugate prior for general target-generated measurement distributions and arbitrary clut…
Deep Fusion of Multi-Object Densities Using Transformer
Lechi Li, Chen Dai, Yuxuan Xia +1
In this paper, we demonstrate that deep learning based method can be used to fuse multi-object densities. Given a scenario with several sensors with possibly different field-of-vie…
A comparison between PMBM Bayesian track initiation and labelled RFS adaptive birth
Ángel F. García-Fernández, Yuxuan Xia, Lennart Svensson
This paper provides a comparative analysis between the adaptive birth model used in the labelled random finite set literature and the track initiation in the Poisson multi-Bernoull…
Trajectory PMB Filters for Extended Object Tracking Using Belief Propagation
Yuxuan Xia, Ángel F. García-Fernández, Florian Meyer +3
In this paper, we propose a Poisson multi-Bernoulli (PMB) filter for extended object tracking (EOT), which directly estimates the set of object trajectories, using belief propagati…
Multiple Object Trajectory Estimation Using Backward Simulation
Yuxuan Xia, Lennart Svensson, Ángel F. García-Fernández +3
This paper presents a general solution for computing the multi-object posterior for sets of trajectories from a sequence of multi-object (unlabelled) filtering densities and a mult…
GNN-PMB: A Simple but Effective Online 3D Multi-Object Tracker without Bells and Whistles
Jianan Liu, Liping Bai, Yuxuan Xia +3
Multi-object tracking (MOT) is among crucial applications in modern advanced driver assistance systems (ADAS) and autonomous driving (AD) systems. The global nearest neighbor (GNN)…