Real-Time Hand Gesture Tracking for Human–Computer Interface Based on Multi-Sensor Data Fusion

Li, Jie; Liu, Xiaofeng; Wang, Zhelong; Zhang, Tingting; Qiu, Sen; Zhao, Hongyu; Zhou, Xiaoqing; Cai, Huili; Ni, Rongrong; Cangelosi, Angelo

doi:10.1109/jsen.2021.3122236

Cited by 20 publications

(6 citation statements)

References 34 publications

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“…Unify and rationally utilize the capabilities of each sensor, reasonably allocate the computing units of each sensor, and comprehensively judge the validity and accuracy of the information [15]. The implementation of MSIF requires the installation of several similar or completely complementary sensors in multiple parts of the smart device to obtain single and incomplete information and then use information fusion algorithms to find possible potential connections among a large amount of data from different sensors [16]. Remove redundant information and form a complete system environment for accurate understanding [17].…”

Section: Introductionmentioning

confidence: 99%

The Application of Multisensor Information Fusion Technology in Environmental Restoration

Youhua

Guo

et al. 2022

Journal of Sensors

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Multisensor information fusion technology is an advanced processing method that is different from classical data processing technology. Capability and operational accuracy, in order to make an effective comprehensive evaluation of environmental quality, the environmental monitoring system built by NB-IoT technology and sensor technology is used to conduct multisensor data fusion research on the collected environmental factors such as temperature, humidity, formaldehyde, PM2.5, and TVOC. At the same time, the two-level parallel fusion method is adopted to evaluate the environmental quality. Before data fusion, median filtering is used to eliminate abnormal data. Then, the Kalman filter algorithm is used to fuse multiple sets of similar sensors to obtain the best value of it. Finally, the fuzzy comprehensive evaluation method is used to fuse the different types of sensors at the decision-making level, in which the weight value is determined by the entropy method and the membership function is Gaussian. The different environment scenarios are tested by using the above algorithms, and the simulation results show that multisensor data fusion can obtain more abundant and effective environmental information, overcome the simplicity and limitation of single-factor sensor for environmental quality assessment, and improve the reliability and accuracy of the overall environmental quality assessment.

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Section: Introductionmentioning

confidence: 99%

The Application of Multisensor Information Fusion Technology in Environmental Restoration

Youhua

Guo

et al. 2022

Journal of Sensors

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“…Additionally, it can contribute to research endeavors focused on motor imagery development when hand motor execution data could be useful, especially when integrated with tools like electroencephalography [48]. Beyond healthcare, hand tracking has implications in gaming [49], human-computer interaction [50], and security/authentication systems [51].…”

Section: Discussionmentioning

confidence: 99%

Portable Head-Mounted System for Mobile Forearm Tracking

Polsinelli,

Di Matteo,

Lozzi

et al. 2024

Sensors

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Computer vision (CV)-based systems using cameras and recognition algorithms offer touchless, cost-effective, precise, and versatile hand tracking. These systems allow unrestricted, fluid, and natural movements without the constraints of wearable devices, gaining popularity in human–system interaction, virtual reality, and medical procedures. However, traditional CV-based systems, relying on stationary cameras, are not compatible with mobile applications and demand substantial computing power. To address these limitations, we propose a portable hand-tracking system utilizing the Leap Motion Controller 2 (LMC) mounted on the head and controlled by a single-board computer (SBC) powered by a compact power bank. The proposed system enhances portability, enabling users to interact freely with their surroundings. We present the system’s design and conduct experimental tests to evaluate its robustness under variable lighting conditions, power consumption, CPU usage, temperature, and frame rate. This portable hand-tracking solution, which has minimal weight and runs independently of external power, proves suitable for mobile applications in daily life.

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“…Evidence Theory. As a mathematical method for dealing with uncertainty reasoning problems, the evidence theory has been widely applied in fields such as multiattribute decision-making [27,28], information fusion [29,30], target tracking [31,32], and fault diagnosis [33,34], due to its flexibility and effectiveness in modeling uncertainty and inaccuracy without prior information. Definition 1.…”

Section: Preliminariesmentioning

confidence: 99%

The Multisensor Data Fusion Method Based on Improved Fuzzy Evidence Theory in the Coal Mine Environment

Wang,

Fu,

2024

Journal of Sensors

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An enhanced evidence theory-based multisensor data fusion technique is presented to address the problem of poor data fusion caused by an unknown interference in the fully automated mining face multisensor system of a coal mine. Initially, the set of all measurement values is considered as the identification framework, and the principles of fuzzy mathematics are applied to introduce the membership function. This leads to the proposal of a novel method for calculating mutual support among multiple sensors. Furthermore, the basic belief assignment (BBA) in evidence theory is determined by measuring the confidence distance between sensors. Subsequently, a divergence measure is employed to assess the level of conflict and difference between BBA functions, which serves as an indicator of their credibility. The credibility of BBA functions is further adjusted by calculating their information volume using Shannon entropy. This adjustment aims to increase the weight of BBA functions that exhibit less conflict with other BBA functions. Ultimately, the fusion result is obtained through an evidence combination rule based on a conflict allocation. The numerical experimental results demonstrate that the proposed approach achieves higher accuracy, better robustness, and generality compared to the existing methods.

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Real-Time Hand Gesture Tracking for Human–Computer Interface Based on Multi-Sensor Data Fusion

Cited by 20 publications

References 34 publications

The Application of Multisensor Information Fusion Technology in Environmental Restoration

The Application of Multisensor Information Fusion Technology in Environmental Restoration

Portable Head-Mounted System for Mobile Forearm Tracking

The Multisensor Data Fusion Method Based on Improved Fuzzy Evidence Theory in the Coal Mine Environment

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