Robust Object Tracking Based on Recurrent Neural Networks

Lotfi, Faraz; Ajallooeian, V.; Taghirad, Hamid D.

doi:10.1109/icrom.2018.8657608

Cited by 10 publications

(7 citation statements)

References 9 publications

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“…To tackle this problem, in this paper a CNN is utilized to detect all potential moving objects through a single image. In addition, considering the reported results in [49],…”

Section: Simulation Resultsmentioning

confidence: 97%

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A Framework for 3D Tracking of Frontal Dynamic Objects in Autonomous Cars

Lotfi¹,

Taghirad²

2021

Preprint

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Both recognition and 3D tracking of frontal dynamic objects are crucial problems in an autonomous vehicle, while depth estimation as an essential issue becomes a challenging problem using a monocular camera. Since both camera and objects are moving, the issue can be formed as a structure from motion (SFM) problem. In this paper, to elicit features from an image, the YOLOv3 approach is utilized beside an OpenCV tracker. Subsequently, to obtain the lateral and longitudinal distances, a nonlinear SFM model is considered alongside a state-dependent Riccati equation (SDRE) filter and a newly developed observation model. Additionally, a switching method in the form of switching estimation error covariance is proposed to enhance the robust performance of the SDRE filter. The stability analysis of the presented filter is conducted on a class of discrete nonlinear systems. Furthermore, the ultimate bound of estimation error caused by model uncertainties is analytically obtained to investigate the switching significance. Simulations are reported to validate the performance of the switched SDRE filter. Finally, real-time experiments are performed through a multi-thread framework implemented on a Jetson TX2 board, while radar data is used for the evaluation.

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“…To tackle this problem, in this paper a CNN is utilized to detect all potential moving objects through a single image. In addition, considering the reported results in [49],…”

Section: Simulation Resultsmentioning

confidence: 97%

“…Since (19) holds, setting ∆V p equal to zero in (53) yields an equation which its solution is the ultimate error bound. Consequently, considering (49) beside (53) results to the following solution:…”

Section: Ultimate Error Bound Analysismentioning

confidence: 99%

A Framework for 3D Tracking of Frontal Dynamic Objects in Autonomous Cars

Lotfi¹,

Taghirad²

2021

Preprint

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“…The introduction of new hardware capable of running deep learning methods with acceptable performance led artificial intelligence to play a more significant role in any intelligent system Han (2017) . It is undeniable that there is a huge potential in employing deep learning methods in a wide range of various applications Weng et al (2019) , Antoniades et al (2016) , Lotfi et al (2018) , Lotfi et al (2020) . In particular, utilizing a camera along with a deep learning algorithm, machines may precisely identify and classify objects by which either performing a proper reaction or monitoring a process may be realized automatically.…”

Section: Machine Visionmentioning

confidence: 99%

Applications of Haptic Technology, Virtual Reality, and Artificial Intelligence in Medical Training During the COVID-19 Pandemic

et al. 2021

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This paper examines how haptic technology, virtual reality, and artificial intelligence help to reduce the physical contact in medical training during the COVID-19 Pandemic. Notably, any mistake made by the trainees during the education process might lead to undesired complications for the patient. Therefore, training of the medical skills to the trainees have always been a challenging issue for the expert surgeons, and this is even more challenging in pandemics. The current method of surgery training needs the novice surgeons to attend some courses, watch some procedure, and conduct their initial operations under the direct supervision of an expert surgeon. Owing to the requirement of physical contact in this method of medical training, the involved people including the novice and expert surgeons confront a potential risk of infection to the virus. This survey paper reviews recent technological breakthroughs along with new areas in which assistive technologies might provide a viable solution to reduce the physical contact in the medical institutes during the COVID-19 pandemic and similar crises.

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“…To realize the visual based manipulator control, the object identication and tracking process are important. CNN was employed for object detection [11] whereas RNN exhibits superior performance for object tracking [12].…”

Section: Introductionmentioning

confidence: 99%

A development of visual-feedback automatic control for robotic manipulator

Nakahara

Thongpull

2022

ECTI-CIT Transactions

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In this work, an automatic robotic manipulator control based on visual information for object tracking is presented. The tracking process employ Recurrent Neural Network and Kalman filter techniques to predict the location of target object which is used to calculate movement of the robot. A manipulator control process was developed to provide consistent motion and reduce vibration. We also propose an object analysis based on image processing technique for object size determination. We implemented the proposed system with an actual robotic manipulator with a gripper for experiments. The experiments shown that object size estimation method results the maximum accuracy at 1.13%. The proposed object tracking and manipulator control process achieved vibration reduction 3.05 times compared to simple control method and reduced the time of end-effector reaching the target object by 1.29sec.

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Robust Object Tracking Based on Recurrent Neural Networks

Cited by 10 publications

References 9 publications

A Framework for 3D Tracking of Frontal Dynamic Objects in Autonomous Cars

A Framework for 3D Tracking of Frontal Dynamic Objects in Autonomous Cars

Applications of Haptic Technology, Virtual Reality, and Artificial Intelligence in Medical Training During the COVID-19 Pandemic

A development of visual-feedback automatic control for robotic manipulator

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