Deterministic Method of Visual Servoing: Robust Object Tracking by Drone

Zakaria, Ouchatti; Bensaid, Alaa; Moutaouakkil, Fouad; Hicham, Medromi

doi:10.1109/cgiv.2016.87

Cited by 2 publications

(2 citation statements)

References 10 publications

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“…The probabilistic method solves the tracking problem based on Bayesian inference or uncertainty modeling, such as Monte Carlo, Particle Filtering framework [21] [22]. Deterministic methods solve the tracking problem by comparison to the region of interest in the present and previous frames [23]. However, the use of an algorithm to track the movement of fireflies has not been reported in firefly flashing behavior studies.…”

Section: Development Of the Program: Firefly Tracking Processmentioning

confidence: 99%

Flash communication pattern analysis of fireflies based on computer vision

Tathawee

Wattanachaiyingcharoen

Suwannakom

et al. 2020

Int. J. Adv. Intell. Informatics

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Previous methods for detecting the flashing behavior of fireflies were using either a photomultiplier tube, a stopwatch, or videography. Limitations and problems are associated with these methods, i.e., errors in data collection and analysis, and it is time-consuming. This study aims to applied a computer vision approach to reduce the time of data collection and analysis as compared to the videography methods by illuminance calculation, time of flash occurrence, and optimize the position coordinate automatically and tracking each firefly individually. The Validation of the approach was performed by comparing the flashing data of male fireflies, Sclerotia aquatilis that was obtained from the analysis of the behavioral video. The pulse duration, flash interval, and flash patterns of S. aquatilis were similar to a reference study. The accuracy ratio of the tracking algorithm for tracking multiple fireflies was 0.94. The time consumption required to analyze the video decreased up to 96.82% and 76.91% when compared with videography and the stopwatch method, respectively. Therefore, this program could be employed as an alternative technique for the study of fireflies flashing behavior.

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Section: Development Of the Program: Firefly Tracking Processmentioning

confidence: 99%

Flash communication pattern analysis of fireflies based on computer vision

Tathawee

Wattanachaiyingcharoen

Suwannakom

et al. 2020

Int. J. Adv. Intell. Informatics

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“…In many cases, whenever it's desired to execute an application autonomously, visual information is commonly very useful. In Zakaria et al (2016), for example, a visual servoing control was implemented using optical flow, which allows tracking moving target objects. However, the computational processing required for these applications usually demands a ground support base.…”

Section: Introductionmentioning

confidence: 99%

A Quadrotor Flight Mode For Tracking Based On Computer Vision Using ROS

Salvador

Silva

Escalfoni

et al. 2019

Anais Do 14º Simpósio Brasileiro De Automação Inteligente

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Unmanned Aerial Vehicles (UAVs) are particularly interesting for covering large areas or observing regions from a privileged angle of view. However, many applications still require direct human control. The addition of visual feedback can enable these vehicles to perform tasks more autonomously. In this context, this work proposes an autonomous flight module, based on computer vision, with embedded processing, to follow a moving target in external environments. Interesting results are obtained through real tests done with a quadcopter that uses Pixhawk for low-level control and a Raspberry Pi for high-level control.

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Deterministic Method of Visual Servoing: Robust Object Tracking by Drone

Cited by 2 publications

References 10 publications

Flash communication pattern analysis of fireflies based on computer vision

Flash communication pattern analysis of fireflies based on computer vision

A Quadrotor Flight Mode For Tracking Based On Computer Vision Using ROS

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