End-to-end active object tracking and its real-world deployment via reinforcement learning

W Luo, P Sun, F Zhong, W Liu… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
We study active object tracking, where a tracker takes visual observations (ie, frame
sequences) as input and produces the corresponding camera control signals as output (eg …

End-to-end active object tracking via reinforcement learning

W Luo, P Sun, F Zhong, W Liu… - … on machine learning, 2018 - proceedings.mlr.press
We study active object tracking, where a tracker takes as input the visual observation (ie
frame sequence) and produces the camera control signal (eg, move forward, turn left, etc) …

Ad-vat+: An asymmetric dueling mechanism for learning and understanding visual active tracking

F Zhong, P Sun, W Luo, T Yan… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
Visual Active Tracking (VAT) aims at following a target object by autonomously controlling
the motion system of a tracker given visual observations. To learn a robust tracker for VAT, in …

AD-VAT: An asymmetric dueling mechanism for learning visual active tracking

F Zhong, P Sun, W Luo, T Yan… - … Conference on Learning …, 2019 - openreview.net
Visual Active Tracking (VAT) aims at following a target object by autonomously controlling
the motion system of a tracker given visual observations. Previous work has shown that the …

Coordinate-aligned multi-camera collaboration for active multi-object tracking

Z Fang, J Zhao, M Yang, Z Lu, W Zhou, H Li - Multimedia Systems, 2024 - Springer
Abstract Active Multi-Object Tracking (AMOT) is a task where cameras are controlled by a
centralized system to adjust their poses automatically and collaboratively so as to maximize …

An improved method based on deep reinforcement learning for target searching

XL Wei, XL Huang, T Lu… - 2019 4th international …, 2019 - ieeexplore.ieee.org
Unmanned Aerial Vehicle (UAV), due to their high mobility and the ability to cover areas of
different heights and locations at relatively low cost, are increasingly used for disaster …

Deep reinforcement learning for autonomous search and rescue

JGC Zuluaga, JP Leidig, C Trefftz… - NAECON 2018-IEEE …, 2018 - ieeexplore.ieee.org
Unmanned Aerial Vehicles (UAVs) are becoming more prevalent, more capable, and less
expensive every day. Advances in battery life and electronic sensors have spurred the …

YOWO: You Only Walk Once to Jointly Map An Indoor Scene and Register Ceiling-mounted Cameras

F Yang, S Yamao, I Kusajima, A Moteki… - … on Circuits and …, 2024 - ieeexplore.ieee.org
Using ceiling-mounted cameras (CMCs) for indoor visual capturing opens up a wide range
of applications. However, registering CMCs to the target scene layout presents a …

Towards active vision for action localization with reactive control and predictive learning

S Trehan, SN Aakur - Proceedings of the IEEE/CVF Winter …, 2022 - openaccess.thecvf.com
Visual event perception tasks such as action localization have primarily focused on
supervised learning settings under a static observer, ie, the camera is static and cannot be …

Effi-MAOT: A Communication-Efficient Multi-Camera Active Object Tracking

M Yin, Z Sun, B Guo, Z Yu - 2023 19th International Conference …, 2023 - ieeexplore.ieee.org
Multi-camera Active Object Tracking (AOT) has become a promising technique to
continuously track the moving target in the intelligent surveillance system. The …