Spatio-Temporal Calibration of Multiple Kinect Cameras Using 3D Human Pose

Eichler, Nadav; Hel‐Or, Hagit; Shimshoni, Ilan

doi:10.3390/s22228900

Cited by 6 publications

(2 citation statements)

References 24 publications

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“…However, multiple infrared cameras are used to capture and integrate 3D data from multiple angles [30], mainly to solve the instability problem when the single camera is collecting data. Compared to a single camera, this approach has little difference in effectiveness for accessibility [31]. Moreover, the markerless method is easy to prepare, which has low equipment costs, and requires less space than the active marking method.…”

Section: Resultsmentioning

confidence: 99%

A New Model for Human Running Micro-Doppler FMCW Radar Features

Zhang

et al. 2023

Applied Sciences

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Human body detection is very important in the research of automotive safety technology. The extraction and analysis of human micro-motion based on frequency-modulated continuous wave (FMCW) radar is gradually receiving attention. Aimed at the modulation effect of human micro-motion on FMCW radar, a human running model is proposed to study human radar characteristics. According to the scattering characteristics of rigid bodies, the analytical expression of human running radar echoes is established. By using time–frequency analysis, the micro-Doppler features in the radar echoes are extracted during the running period. Under running conditions, the micro-Doppler characteristics of key components are studied. This model is applied to the real FMCW radar verification platform, and the runners are measured at a distance of 10 m. The fit rate of all parts of the human body can reach above 90%. The overall fit rate of the human model can reach up to 90.6%. The model proposed is a realistic and simple human kinematic model. This model, which can realize the real simulation of a running human body and provide strong support for human target radar echo analysis, can fill the deficiency of FMCW radar technology in the complex motion model.

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Section: Resultsmentioning

confidence: 99%

A New Model for Human Running Micro-Doppler FMCW Radar Features

Zhang

et al. 2023

Applied Sciences

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“…A pair of Intel Real Sense D435 depth cameras are used (however, one can use any RGB camera for this purpose). The color images obtained from both cameras are used as input to determine the pose of a person [71], [72].…”

Section: B Stereo Vision Modulementioning

confidence: 99%

AI Trainer: Autoencoder Based Approach for Squat Analysis and Correction

Chariar,

Rao,

Irani

et al. 2023

IEEE Access

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Artificial intelligence and computer vision have widespread applications in workout analysis. It has been extensively used in sports and the athlete industry to identify errors and improve performance. Furthermore, these methods prevent injuries caused by a lack of instructors or costly infrastructure. One such exercise is the squat, which is a movement in which a standing person descends to a posture with their torso vertical and their knees firmly bent, then returns to their original upright position. Each person's squat is distinct, with varying limb lengths causing their form to change when observed. It has been observed that the mobility of various joints and muscular strength have a role in this. A squat improves the user by increasing overall leg strength, strengthening knee and hip joints, and lowering the risk of heart disease due to cardiovascular development. This paper presents a method for classifying squat types and recommending the right squat version. This study uses MediaPipe and a deep learning-based technique to decide if squatting is good or bad. A stacked Bidirectional Gated Recurrent Unit (Bi-GRU) model with an attention layer is proposed to consistently and fairly assess each user, categorizing squats into seven classes. This stacked Bi-GRU model with an attention unit is then compared to other cutting-edge models, both with and without the attention layer. The model outperforms other models by attaining an accuracy of 94% and is demonstrated to work the best and most consistently for our dataset. Furthermore, the individual executing the incorrect squat is corrected to the best of their ability, depending on their performance and body proportions, by providing the correct form.

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Platform Design for Optical Screening and Conditioning for Injury Resilience

Shiwani,

Silder,

Tulskie

et al. 2024

Military Medicine

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Introduction Musculoskeletal injuries (MSKIs) among active duty soldiers result in more than 10 million limited duty days each year and account for more than 70% of the medically nondeployable population. Overuse injuries in lower limbs from running, foot marching long distances with heavy loads, and lifting heavy objects are the most common types of injuries in the military. Physical training and rehabilitation exercises for greater resiliency through aerobic, muscle strength, endurance, and agility conditioning programs can prevent or reduce the effects of MSKIs if Soldiers adhere to proper biomechanics and training techniques. We are introducing a three-dimensional (3D) camera-based platform for Optical Screening and Conditioning for Injury Resilience (OSCIR) that is designed to identify and correct high-risk movement patterns based on quantifiable biomechanical measurements in clinical or field settings. Our goal is to improve resilience to MSKI by offering greater access to quality of movement skills in warfighters through an autonomous device that can be used in Sports Medicine and Reconditioning Team (SMART) clinics and High-Intensity Tactical Training (HITT) sites. Materials and Methods OSCIR fuses four pairs of Kinect Azure cameras into a concise footprint to achieve suitable sampling rates and an unobstructed field of view for accurate dynamic movement tracking using a custom point cloud solution. We designed a unique multistage 3D joint tracking algorithm architecture to methodically isolate the human body point cloud from the background, identify individual limb segments, and perform iterative joint optimization at the global and local joint levels. We evaluated the feasibility of our prototype system among N = 12 control participants (6 M/6 F; 21-37 years) in compliance with the Western Institutional Review Board (Tracking #20225920, approved on November 4, 2022). Five task-specific MSKI outcome metrics identified by end-user physical therapists and athletic trainers as indicators for movement quality were assessed across 7 lower-extremity exercises derived from standardized MSK assessment/conditioning batteries used in the military. Data were recorded concurrently by OSCIR and a reference standard Vicon motion capture system for validating system accuracy. Results Task-specific MSKI indicators for knee flexion and hip flexion range of motion achieved an average error of 4.05 ± 2.34°, while 3D position-based postural outcomes of left-right foot distance, left-right hand distance, and step length obtained mean absolute errors of 2.58 ± 2.30 cm. Results support the feasibility of our system in achieving outcomes that are comparable to currently accepted laboratory standards. Conclusions Our study describes the integration process for a 3D camera-based clinical system for MSKI conditioning and rehabilitation. The impact of our system will enable key stakeholders in the military to manage MSKIs in warfighters by automating key assessment and rehabilitation test batteries; making tests more readily accessible, and interpretations more accurate by providing objective biomechanical measures. OSCIR is undergoing turn-key design features to serve as a screening tool for warfighters to readily assess susceptibility to MSKI or as a training platform to help guide exercise techniques to achieve resiliency against future injuries.

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Spatio-Temporal Calibration of Multiple Kinect Cameras Using 3D Human Pose

Cited by 6 publications

References 24 publications

A New Model for Human Running Micro-Doppler FMCW Radar Features

A New Model for Human Running Micro-Doppler FMCW Radar Features

AI Trainer: Autoencoder Based Approach for Squat Analysis and Correction

Platform Design for Optical Screening and Conditioning for Injury Resilience

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