☆ 4.4 Article

Bilateral association tracking with parzen window density estimation

IET IMAGE PROCESSING (2023)

Related references

Note: Only part of the references are listed.

Article Computer Science, Artificial Intelligence

HOTA: A Higher Order Metric for Evaluating Multi-object Tracking

Jonathon Luiten et al.

Summary: The higher order tracking accuracy (HOTA) is a novel evaluation metric for multi-object tracking that balances accurate detection, association, and localization. It decomposes into sub-metrics to evaluate different error types separately, providing clear analysis of tracking performance. The HOTA scores align better with human visual evaluation of tracking performance compared to established metrics.

INTERNATIONAL JOURNAL OF COMPUTER VISION (2021)

Add to Collection

Article Chemistry, Analytical

Robust Data Association Using Fusion of Data-Driven and Engineered Features for Real-Time Pedestrian Tracking in Thermal Images

Mircea Paul Muresan et al.

Summary: Object tracking in thermal images poses challenges due to lack of color data, low image resolution, and high object similarity. This study focused on addressing the data association problem in multi-object tracking, proposing solutions such as data-driven appearance score, edge-based descriptor, and a dataset for training Siamese networks. The combination of data-driven approach and feature engineering led to a more robust and adaptable tracking solution with promising results in real-world scenarios.

SENSORS (2021)

Add to Collection

Article Chemistry, Analytical

Dynamic Object Tracking on Autonomous UAV System for Surveillance Applications

Li-Yu Lo et al.

Summary: This paper presents a learning-based UAV system for autonomous surveillance, utilizing the YOLOv4-Tiny algorithm and integrating 3D object pose estimation and Kalman filter to enhance perception performance. The fully autonomous system includes UAV path planning and is validated through flight experiments, demonstrating robustness, effectiveness, and reliability in performing surveillance tasks.

SENSORS (2021)

Add to Collection

Proceedings Paper Computer Science, Artificial Intelligence

A General Recurrent Tracking Framework without Real Data

Shuai Wang et al.

Summary: A Multiple Nodes Tracking (MNT) framework is proposed in this paper, which is adaptable to most trackers. A Recurrent Tracking Unit (RTU) is designed based on this framework to score potential tracks using long-term information. The method of generating simulated tracking data is presented to overcome the limited available data in MOT, showing effectiveness in training RTU and achieving state-of-the-art performance on MOT benchmarks.

2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2021) (2021)

Add to Collection

Proceedings Paper Automation & Control Systems

Joint Object Detection and Multi-Object Tracking with Graph Neural Networks

Yongxin Wang et al.

Summary: Object detection and data association are critical components in multi-object tracking systems. Recent works have shown that simultaneously optimizing detection and data association modules under a joint MOT framework can lead to improved performance. This study proposes a new instance of joint MOT approach based on Graph Neural Networks, which can model relations between variable-sized objects in both spatial and temporal domains, leading to state-of-the-art performance for both detection and MOT tasks.

2021 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2021) (2021)

Add to Collection

Article Engineering, Electrical & Electronic

End-to-End Learning Deep CRF Models for Multi-Object Tracking Deep CRF Models

Jun Xiang et al.

Summary: This paper proposes utilizing deep conditional random field networks to address the assignment problem in multi-object tracking, optimizing unary and pairwise potentials jointly in an end-to-end learning process. Extensive experiments show that this approach outperforms existing methods on MOT datasets.

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY (2021)

Add to Collection

Article Engineering, Civil

Online Multi-Object Tracking Using Joint Domain Information in Traffic Scenarios

Wei Tian et al.

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2020)

Add to Collection

Article Computer Science, Artificial Intelligence

Long-Term Tracking With Deep Tracklet Association

Yang Zhang et al.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2020)

Add to Collection

Article Engineering, Electrical & Electronic

Deep Continuous Conditional Random Fields With Asymmetric Inter-Object Constraints for Online Multi-Object Tracking

Hui Zhou et al.

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY (2019)

Add to Collection

Article Engineering, Electrical & Electronic

Heterogeneous Association Graph Fusion for Target Association in Multiple Object Tracking

Hao Sheng et al.

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY (2019)

Add to Collection

Article Engineering, Electrical & Electronic

Iterative Multiple Hypothesis Tracking With Tracklet-Level Association

Hao Sheng et al.

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY (2019)

Add to Collection

Proceedings Paper Computer Science, Artificial Intelligence

Video Instance Segmentation 2019: A winning approach for combined Detection, Segmentation, Classification and Tracking

Jonathon Luiten et al.

2019 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW) (2019)

Add to Collection

Article Chemistry, Analytical

Multi-Object Tracking with Correlation Filter for Autonomous Vehicle

Dawei Zhao et al.

SENSORS (2018)

Add to Collection

Article Engineering, Electrical & Electronic

Semi-Online Multiple Object Tracking Using Graphical Tracklet Association

Jiahui Wang et al.

IEEE SIGNAL PROCESSING LETTERS (2018)

Add to Collection

Proceedings Paper Computer Science, Artificial Intelligence

A Directed Sparse Graphical Model for Multi-Target Tracking

Mohib Ullah et al.

PROCEEDINGS 2018 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW) (2018)

Add to Collection

Article Computer Science, Artificial Intelligence

Tracklet Association by Online Target-Specific Metric Learning and Coherent Dynamics Estimation

Bing Wang et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2017)

Add to Collection

Proceedings Paper Computer Science, Artificial Intelligence

Online Multi-Object Tracking Using CNN-based Single Object Tracker with Spatial-Temporal Attention Mechanism

Qi Chu et al.

2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV) (2017)

Add to Collection

Proceedings Paper Computer Science, Artificial Intelligence

Near-Online Multi-target Tracking with Aggregated Local Flow Descriptor

Wongun Choi

2015 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV) (2015)

Add to Collection

Article Computer Science, Artificial Intelligence

Multi-Target Tracking by Online Learning a CRF Model of Appearance and Motion Patterns

Bo Yang et al.

INTERNATIONAL JOURNAL OF COMPUTER VISION (2014)

Add to Collection

Proceedings Paper Computer Science, Artificial Intelligence

Multi-target Tracking by Lagrangian Relaxation to Min-Cost Network Flow

Asad A. Butt et al.

2013 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR) (2013)

Add to Collection

Proceedings Paper Automation & Control Systems

Robust Tracking-by-Detection using a Detector Confidence Particle Filter

Michael D. Breitenstein et al.

2009 IEEE 12TH INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV) (2009)

Add to Collection

© Peeref 2019-2024. All rights reserved.