Designing a camera placement assistance system for human motion capture based on a guided genetic algorithm

Aissaoui, Azeddine; Ouafi, Abdelkrim; Pudlo, Philippe; Gillet, Christophe; Baarir, Zine-Eddine; Taleb‐Ahmed, Abdelmalik

doi:10.1007/s10055-017-0310-7

Cited by 15 publications

(9 citation statements)

References 21 publications

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“…Recently, the camera placement problems have been extended to multiobjective optimization that not only maximizes cameras' coverage but also minimizes investment costs (Ahn et al 2016;Altahir et al 2017;Zhao et al 2013). To solve the defined problems with a reasonable practical range of accuracy, researchers have also tested the applicability of metaheuristic optimization algorithms for camera placement (Abdesselam and Baarir 2018;Aissaoui et al 2017;Al-Hmouz and Challa 2005). Building on previous research, camera placement optimization techniques were further leveraged for a series of domain-specific applications.…”

Section: Art Gallery Problems For Camera Placement and Current Practimentioning

confidence: 99%

“…The camera placement problem is known to be a nondeterministic polynomial time hard (NP-hard problem) (Cole and Sharir 1989;O'Rourke 1987) that has high dimensionality of the search space and nonlinearity among decision variables, objective functions, and constraints (Aissaoui et al 2017). This statement infers that simple iterative search algorithms will most likely have difficulty finding the optimal solution.…”

Section: Hybrid Simulation-optimization Of Camera Placement On Constrmentioning

confidence: 99%

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Systematic Camera Placement Framework for Operation-Level Visual Monitoring on Construction Jobsites

Kim

Ham

Chung³

et al. 2019

J. Constr. Eng. Manage.

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This paper proposes a camera placement framework that incorporates characteristics of complex construction jobsites. The proposed framework consists of three main processes: (1) identification of visual monitoring determinants, influencing factors, and camera placement conditions; (2) problem definition and mathematical modeling; and (3) hybrid simulation-optimization of camera placement on construction jobsites. To evaluate the performance of the proposed framework, a case study for an actual construction jobsite was performed. The results of the case study show the potential of the proposed framework to find the optimal number, types, locations, and orientations of cameras for jobsite visual monitoring. This research makes three main contributions: (1) identification of critical elements to be considered when installing fixed cameras on complex construction jobsites; (2) development of a systematic framework for camera placement on jobsites; and (3) visualization and quantification of multiple camera network designs and their performance (i.e., total costs and visible coverages) before installing cameras at actual jobsites.

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Section: Art Gallery Problems For Camera Placement and Current Practimentioning

confidence: 99%

Section: Hybrid Simulation-optimization Of Camera Placement On Constrmentioning

confidence: 99%

Systematic Camera Placement Framework for Operation-Level Visual Monitoring on Construction Jobsites

Kim

Ham

Chung³

et al. 2019

J. Constr. Eng. Manage.

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“…In the last decade, many researchers have developed devices and systems to monitor human motion and activity recognition. Although a number of these systems (e.g., 3D motion analysis) provide accurate information, they are often expensive and limited to laboratory settings [5]. Others [6,7] have used machine learning techniques, which often require the attachment of multiple inertial measurement unit (IMU) sensors to detect the motion.…”

Section: Introductionmentioning

confidence: 99%

Human Movement Monitoring and Analysis for Prehabilitation Process Management

Al-Naime

Al-Anbuky

Mawston

2020

JSAN

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Cancer patients assigned for abdominal surgery are often given exercise programmes (prehabilitation) prior to surgery, which aim to improve fitness in order to reduce pre-operative risk. However, only a small proportion of patients are able to partake in supervised hospital-based prehabilitation because of inaccessibility and a lack of resources, which often makes it difficult for health professionals to accurately monitor and provide feedback on exercise and activity levels. The development of a simple tool to detect the type and intensity of physical activity undertaken outside the hospital setting would be beneficial to both patients and clinicians. This paper aims to describe the key exercises of a prehabilitation programme and to determine whether the types and intensity of various prehabilitation exercises could be accurately identified using Fourier analysis of 3D accelerometer sensor data. A wearable sensor with an inbuilt 3D accelerometer was placed on both the ankle and wrist of five volunteer participants during nine prehabilitation exercises which were performed at low to high intensity. Here, the 3D accelerometer data are analysed using fast Fourier analysis, where the dominant frequency and amplitude components are extracted for each activity performed at low, moderate, and high intensity. The findings indicate that the 3D accelerometer located at the ankle is suitable for detecting activities such as cycling and rowing at low, moderate, and high exercise intensities. However, there is some overlap in the frequency and acceleration amplitude components for overland and treadmill walking at a moderate intensity.

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“…Then, using the basic configuration (without reducing the number of cameras), the acquisition volume is calculated without and with optimization of the location of the cameras. To optimize the location of the cameras, the GGA method of Aissaoui et al (2017) is applied (Figure 1). …”

Section: Methodsmentioning

confidence: 99%

“…The algorithm allows to find the tags arranged on a virtual humanoid, in the same place as the markers affixed on the real subject, and which simulates a neighbouring movement of the movement to be studied. Since then, this algorithm has been developed, as described in Aissaoui et al (2017). In continuity, 2 questions arise:…”

Section: Introductionmentioning

confidence: 99%

Reducing the number of cameras and increasing the calibrated volume for motion capture

Aissaoui

Pudlo

Aloui

et al. 2017

Computer Methods in Biomechanics and Biomedical Engineering

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Designing a camera placement assistance system for human motion capture based on a guided genetic algorithm

Cited by 15 publications

References 21 publications

Systematic Camera Placement Framework for Operation-Level Visual Monitoring on Construction Jobsites

Systematic Camera Placement Framework for Operation-Level Visual Monitoring on Construction Jobsites

Human Movement Monitoring and Analysis for Prehabilitation Process Management

Reducing the number of cameras and increasing the calibrated volume for motion capture

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