Research on realizing the 3D occlusion tracking location method of fish's school target

Mao, Jiafa; Xiao, Gang; Sheng, Weiguo; Qu, Zhiguo; Liu, Yurong

doi:10.1016/j.neucom.2016.05.067

Cited by 17 publications

(12 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several studies have used fish as an inspiration in approaching problems in complex optimization domains [40], such as networks [41][42][43][44][45], image processing [46][47][48], robotics, motion control [49][50][51], machine learning [52][53][54], path planning [55,56], industries [57], automation [58], and many other fields. However, few fish-inspired heuristics have been proposed, particularly targeting the task allocation problem.…”

Section: Related Workmentioning

confidence: 99%

Fish-Inspired Task Allocation Algorithm for Multiple Unmanned Aerial Vehicles in Search and Rescue Missions

Alhaqbani

Kurdi

2020

Remote Sensing

View full text Add to dashboard Cite

The challenge concerning the optimal allocation of tasks across multiple unmanned aerial vehicles (multi-UAVs) has significantly spurred research interest due to its contribution to the success of various fleet missions. This challenge becomes more complex in time-constrained missions, particularly if they are conducted in hostile environments, such as search and rescue (SAR) missions. In this study, a novel fish-inspired algorithm for multi-UAV missions (FIAM) for task allocation is proposed, which was inspired by the adaptive schooling and foraging behaviors of fish. FIAM shows that UAVs in an SAR mission can be similarly programmed to aggregate in groups to swiftly survey disaster areas and rescue-discovered survivors. FIAM’s performance was compared with three long-standing multi-UAV task allocation (MUTA) paradigms, namely, opportunistic task allocation scheme (OTA), auction-based scheme, and ant-colony optimization (ACO). Furthermore, the proposed algorithm was also compared with the recently proposed locust-inspired algorithm for MUTA problem (LIAM). The experimental results demonstrated FIAM’s abilities to maintain a steady running time and a decreasing mean rescue time with a substantially increasing percentage of rescued survivors. For instance, FIAM successfully rescued 100% of the survivors with merely 16 UAVs, for scenarios of no more than eight survivors, whereas LIAM, Auction, ACO and OTA rescued a maximum of 75%, 50%, 35% and 35%, respectively, for the same scenarios. This superiority of FIAM performance was maintained under a different fleet size and number of survivors, demonstrating the approach’s flexibility and scalability.

show abstract

Section: Related Workmentioning

confidence: 99%

Fish-Inspired Task Allocation Algorithm for Multiple Unmanned Aerial Vehicles in Search and Rescue Missions

Alhaqbani

Kurdi

2020

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…This method can accurately reconstruct the fish’s body position, curvature and direction from multiple viewpoints. Mao et al [ 18 ] designed a multiple fish information acquisition platform by using a camera and a mirror. Based on the platform, they proposed an automated video tracking method which can solve the occlusion tracking problem of multiple fish in 3D space.…”

Section: Related Workmentioning

confidence: 99%

Feature point based 3D tracking of multiple fish from multi-view images

Qian

Chen

2017

PLoS ONE

View full text Add to dashboard Cite

A feature point based method is proposed for tracking multiple fish in 3D space. First, a simplified representation of the object is realized through construction of two feature point models based on its appearance characteristics. After feature points are classified into occluded and non-occluded types, matching and association are performed, respectively. Finally, the object's motion trajectory in 3D space is obtained through integrating multi-view tracking results. Experimental results show that the proposed method can simultaneously track 3D motion trajectories for up to 10 fish accurately and robustly.

show abstract

“…Target tracking technology is widely used in military guidance [1,2], virtual reality [3], video surveillance [4], medical diagnosis [5], robot control [6] and other scientific fields. Target occlusion has always been one of the most challenging problems in target tracking [7,8]. In the electro-optical tracking system, target tracking means that the line of sight (LOS) of the system follows the target [9].…”

Section: Introductionmentioning

confidence: 99%

A target anti‐occlusion method based on image processing and trajectory prediction in electro‐optical tracking system

Xia

Duan

Deng

et al. 2022

IET Radar Sonar & Navi

View full text Add to dashboard Cite

In the electro-optical tracking system, due to the full occlusion of clouds or buildings, the traditional tracking algorithm fails to work effectively. In the authors' study, a dualchannel anti-occlusion scheme based on image processing and trajectory prediction is proposed. On the one hand, the image-processing unit plays a significant role in evaluating the occlusion state of the target. An improved image occlusion judgement method based on Bhattacharyya coefficient occlusion judgement is proposed, and the ability to resist background interference and rapidity of the algorithm is enhanced. On the other hand, according to the different occlusion states, the dual operation modes of tracking and prediction are usually set. When the target is completely occluded, the prediction mode based on a robust predictive filtering method is investigated to predict the real-time trajectory of the target more accurately. Image occlusion judgement and trajectory prediction can solve the occlusion problems in tracking control. Otherwise, the feasibility and effectiveness of the proposed method are verified by experiments. The cover image is based on the Research Article A target anti-occlusion method based on image processing and trajectory prediction in electro-optical tracking system by Yao Mao et al., https://doi.org/10.1049/rsn2.12235. K E Y W O R D S anti occlusion, electro-optical tracking system, image occlusion judgement, robust predictive filtering, trajectory predictionThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

show abstract

Research on realizing the 3D occlusion tracking location method of fish's school target

Cited by 17 publications

References 30 publications

Fish-Inspired Task Allocation Algorithm for Multiple Unmanned Aerial Vehicles in Search and Rescue Missions

Fish-Inspired Task Allocation Algorithm for Multiple Unmanned Aerial Vehicles in Search and Rescue Missions

Feature point based 3D tracking of multiple fish from multi-view images

A target anti‐occlusion method based on image processing and trajectory prediction in electro‐optical tracking system

Contact Info

Product

Resources

About