no code implementations • 27 Apr 2024 • Jiayin Deng, Zhiqun Hu, Yuxuan Xia, Zhaoming Lu, Xiangming Wen
In this paper, we present a novel three-dimensional (3D) extended object tracking (EOT) method, which simultaneously estimates the object kinematics and extent state, in roadside perception using both the radar and camera data.
no code implementations • 11 Mar 2024 • Guanhua Ding, Jianan Liu, Yuxuan Xia, Tao Huang, Bing Zhu, Jinping Sun
Simulation results illustrate the superior estimation accuracy of the proposed PMRA-PMBM filter in terms of both positions and extents of the vehicles comparing with PMBM filters using the gamma Gaussian inverse Wishart and DRA implementations.
no code implementations • 18 Jan 2024 • Li Guo, Haoming Liu, Yuxuan Xia, Chengyu Zhang, Xiaochen Lu
On the other hand, the large visual difference between query and support images may hinder knowledge transfer and cripple the segmentation performance.
no code implementations • 22 Dec 2023 • Juliano Pinto, Georg Hess, Yuxuan Xia, Henk Wymeersch, Lennart Svensson
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.
no code implementations • 6 Dec 2023 • 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.
no code implementations • 5 Oct 2023 • Tao Huang, Jianan Liu, Xi Zhou, Dinh C. Nguyen, Mostafa Rahimi Azghadi, Yuxuan Xia, Qing-Long Han, Sumei Sun
To address this gap, this paper provides a comprehensive overview of the evolution of CP technologies, spanning from early explorations to recent developments, including advancements in V2X communication technologies.
no code implementations • 12 Sep 2023 • Jianan Liu, Guanhua Ding, Yuxuan Xia, Jinping Sun, Tao Huang, Lihua Xie, Bing Zhu
These provide the first benchmark and important insights for the future development of 4D imaging radar-based online 3D MOT algorithms.
no code implementations • 19 Aug 2023 • Zhenrong Zhang, Jianan Liu, Yuxuan Xia, Tao Huang, Qing-Long Han, Hongbin Liu
The state-of-the-art approaches usually employ a tracking-by-detection method, and data association plays a critical role.
1 code implementation • 1 Aug 2023 • Yuelin Xin, Zihan Zhou, Yuxuan Xia
We present 2SDS (Scene Separation and Data Selection algorithm), a temporal segmentation algorithm used in real-time video stream interpretation.
no code implementations • 3 Jul 2023 • Weiyi Xiong, Jianan Liu, Tao Huang, Qing-Long Han, Yuxuan Xia, Bing Zhu
They are sent to the core of LXL, called "radar occupancy-assisted depth-based sampling", to aid image view transformation.
no code implementations • 5 May 2023 • Hyowon Kim, Angel F. García-Fernández, Yu Ge, Yuxuan Xia, Lennart Svensson, Henk Wymeersch
In this paper, we develop BP rules for factor graphs defined on sequences of RFSs where each RFS has an unknown number of elements, with the intention of deriving novel inference methods for RFSs.
Simultaneous Localization and Mapping Vocal Bursts Type Prediction
1 code implementation • 19 Sep 2022 • Lechi Li, Chen Dai, Yuxuan Xia, Lennart Svensson
We compare the performance of the transformer-based fusion method with a well-performing model-based Bayesian fusion method in several simulated scenarios with different parameter settings using synthetic data.
1 code implementation • 20 Jul 2022 • Yuxuan Xia, Ángel F. García-Fernández, Florian Meyer, Jason L. Williams, Karl Granström, Lennart Svensson
First, we present a PMBM conjugate prior on the posterior of sets of trajectories for a generalized measurement model, in which each object generates an independent set of measurements.
1 code implementation • 13 Jul 2022 • 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-Bernoulli mixture (PMBM) filter, with point-target models.
1 code implementation • 21 Jun 2022 • Jianan Liu, Liping Bai, Yuxuan Xia, Tao Huang, Bing Zhu, Qing-Long Han
The global nearest neighbor (GNN) filter, as the earliest random vector-based Bayesian tracking framework, has been adopted in most of state-of-the-arts trackers in the automotive industry.
no code implementations • 16 Jun 2022 • Yuxuan Xia, Lennart Svensson, Ángel F. García-Fernández, Jason L. Williams, Daniel Svensson, Karl Granström
In this paper, we first derive a general multi-trajectory backward smoothing equation based on random finite sets of trajectories.
no code implementations • 13 Mar 2022 • Weiyi Xiong, Jianan Liu, Yuxuan Xia, Tao Huang, Bing Zhu, Wei Xiang
Deep learning-based instance segmentation enables real-time object identification from the radar detection points.
1 code implementation • 16 Feb 2022 • Juliano Pinto, Georg Hess, William Ljungbergh, Yuxuan Xia, Henk Wymeersch, Lennart Svensson
Multi-object tracking (MOT) is the problem of tracking the state of an unknown and time-varying number of objects using noisy measurements, with important applications such as autonomous driving, tracking animal behavior, defense systems, and others.
no code implementations • 5 Oct 2021 • Jianan Liu, Weiyi Xiong, Liping Bai, Yuxuan Xia, Tao Huang, Wanli Ouyang, Bing Zhu
Automotive radar provides reliable environmental perception in all-weather conditions with affordable cost, but it hardly supplies semantic and geometry information due to the sparsity of radar detection points.
no code implementations • 10 Aug 2021 • Juliano Pinto, Yuxuan Xia, Lennart Svensson, Henk Wymeersch
Evaluating the performance of multi-object tracking (MOT) methods is not straightforward, and existing performance measures fail to consider all the available uncertainty information in the MOT context.
1 code implementation • 1 Apr 2021 • Juliano Pinto, Georg Hess, William Ljungbergh, Yuxuan Xia, Lennart Svensson, Henk Wymeersch
We show that the proposed model outperforms state-of-the-art Bayesian filters in complex scenarios, while matching their performance in simpler cases, which validates the applicability of deep-learning also in the model-based regime.
1 code implementation • 9 Nov 2020 • Ángel F. García-Fernández, Jason L. Williams, Lennart Svensson, Yuxuan Xia
This paper proposes a Poisson multi-Bernoulli mixture (PMBM) filter for coexisting point and extended targets, i. e., for scenarios where there may be simultaneous point and extended targets.
no code implementations • 5 Aug 2020 • Yuxuan Xia, Lennart Svensson, Ángel F. García-Fernández, Karl Granström, Jason L. Williams
This paper presents a solution for recovering full trajectory information, via the calculation of the posterior of the set of trajectories, from a sequence of multitarget (unlabelled) filtering densities and the multitarget dynamic model.
no code implementations • 28 Mar 2020 • Ángel F. García-Fernández, Lennart Svensson, Jason L. Williams, Yuxuan Xia, Karl Granström
The filters are based on propagating a Poisson multi-Bernoulli (PMB) density on the corresponding set of trajectories through the filtering recursion.
1 code implementation • 17 Dec 2019 • Karl Granström, Lennart Svensson, Yuxuan Xia, Jason Williams, Ángel F. García-Fernández
First, we show that, for the standard point target model, the PMBM density is conjugate also for sets of trajectories.
1 code implementation • 4 Dec 2019 • Yuxuan Xia, Karl Granström, Lennart Svensson, Ángel F. García-Fernández, Jason L. Williams
A multi-scan trajectory PMBM filter and a multi-scan trajectory MBM filter, with the ability to correct past data association decisions to improve current decisions, are presented.
Signal Processing
2 code implementations • 19 Nov 2019 • Yuxuan Xia, Karl Granström, Lennart Svensson, Ángel F. García-Fernández, Jason L. Williams
The Poisson multi-Bernoulli mixture (PMBM) is a multi-target distribution for which the prediction and update are closed.
Signal Processing
1 code implementation • 23 Aug 2019 • Ángel F. García-Fernández, Yuxuan Xia, Karl Granström, Lennart Svensson, Jason L. Williams
This paper presents the Gaussian implementation of the multi-Bernoulli mixture (MBM) filter.
3 code implementations • 12 Dec 2018 • Karl Granström, Lennart Svensson, Yuxuan Xia, Jason Williams, Angel F Garcia-Fernandez
By showing that the prediction and update in the PMBM filter can be viewed as an efficient method for calculating the time marginals of the RFS of trajectories, continuity in the same sense as MHT is established for the PMBM filter.
1 code implementation • 29 Nov 2018 • Yuxuan Xia, Karl Granström, Lennart Svensson, Ángel F. García-Fernández
This paper proposes an efficient implementation of the Poisson multi-Bernoulli mixture (PMBM) trajectory filter.
1 code implementation • 4 Jan 2018 • Yuxuan Xia, Karl Granström, Lennart Svensson, Maryam Fatemi, Ángel F. García-Fernández, Jason L. Williams
The Poisson multi-Bernoulli mixture (PMBM) is a multi-object conjugate prior for the closed-form Bayes random finite sets filter.