Human–Computer Interaction for Smart Environment Applications Using Fuzzy Hand Posture and Gesture Models

Várkonyi-Kóczy, Annamária R.; Tusor, Balazs

doi:10.1109/tim.2011.2108075

Cited by 68 publications

(21 citation statements)

References 8 publications

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“…A few works [142,143,144] on fusing the fuzzy approaches with machine learning solutions have been reported in the gesture recognition. [142] used the adaptive neuro-fuzzy inference system to recognize the gestures in Arabic sign language.…”

Section: Hybrid Techniquementioning

confidence: 99%

“…The proposed method reduced the system complexity and performed in real-time manner. Nonetheless, [144] presented an approach with several novelties and advantages as compared to other hybrid solutions. They introduced a new fuzzy hand-posture model using a modified circular fuzzy neural network architecture to efficiently recognize the hand posture.…”

Section: Hybrid Techniquementioning

confidence: 99%

“…[142,143,144] Integration of the fuzzy approaches with machine learning algorithms help in learning the important parameters for the fuzzy system adaptively based on the training data.…”

Section: Fuzzy Clusteringmentioning

confidence: 99%

See 2 more Smart Citations

Fuzzy human motion analysis: A review

Lim

Vats

Chan

2015

Pattern Recognition

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Human Motion Analysis (HMA) is currently one of the most popularly active research domains as such significant research interests are motivated by a number of real world applications such as video surveillance, sports analysis, healthcare monitoring and so on. However, most of these real world applications face high levels of uncertainties that can affect the operations of such applications. Hence, the fuzzy set theory has been applied and showed great success in the recent past. In this paper, we aim at reviewing the fuzzy set oriented approaches for HMA, individuating how the fuzzy set may improve the HMA, envisaging and delineating the future perspectives. To the best of our knowledge, there is not found a single survey in the current literature that has discussed and reviewed fuzzy approaches towards the HMA. For ease of understanding, we conceptually classify the human motion into three broad levels: Low-Level (LoL), Mid-Level (MiL), and High-Level (HiL) HMA.

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Section: Hybrid Techniquementioning

confidence: 99%

Section: Hybrid Techniquementioning

confidence: 99%

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Fuzzy human motion analysis: A review

Lim

Vats

Chan

2015

Pattern Recognition

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“…Prior to developing those predictors, an appropriate on-road sensor configuration, which illustrates the on-road sensor locations and the number of on-road sensors, has to be determined. Even though reasonable results can be obtained using statistical methods [3], [19], [20], [26], and more convincing results can be obtained using the universal estimator [18], [24], namely, fuzzy neural networks (FNNs) [4], [12], [27], the determination of an appropriate on-road sensor configuration has yet to be resolved.…”

Section: Introductionmentioning

confidence: 99%

On-Road Sensor Configuration Design for Traffic Flow Prediction Using Fuzzy Neural Networks and Taguchi Method

Chan

Dillon

2013

IEEE Trans. Instrum. Meas.

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On-road sensors provide proactive traffic control centers with current traffic flow conditions in order to forecast the future conditions. However, the number of on-road sensors is usually huge, and not all traffic flow conditions captured by these sensors are useful for predicting future traffic flow conditions. The inclusion of all captured traffic flow conditions is an ineffective means of predicting future traffic flow. Therefore, the selection of appropriate on-road sensors, which are significantly correlated to future traffic flow, is essential, although the trial and error method is generally used for the selection. In this paper, the Taguchi method, which is a robust and systematic optimization approach for designing reliable and high-quality models, is proposed for determinations of appropriate on-road sensors, in order to capture useful traffic flow conditions for forecasting. The effectiveness of the Taguchi method is demonstrated by developing a traffic flow predictor based on the architecture of fuzzy neural networks which can perform well on traffic flow forecasting. The case study was conducted based on traffic flow data captured by on-road sensors located on a Western Australia freeway. The advantages of using the Taguchi method can be indicated: 1) Traffic flow predictors with high accuracy can be designed, and 2) development time of traffic flow predictors is reasonable.Index Terms-Fuzzy neural networks (FNNs), fuzzy systems, on-road sensor, orthogonal array, sensor configuration, Taguchi method, traffic flow control, traffic flow prediction.

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“…The first method is to build the gesture model by using the 2D gray image itself [4]. The second method is to utilize the deformable 2D template [5]. The third method is based on the attributes of the image [6].…”

Section: Introductionmentioning

confidence: 99%

Hand Gesture Recognition Based on Fingertip Detection

Guoqing-Meng¹,

Wang²

2013

2013 Fourth Global Congress on Intelligent Systems

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To improve the hand gesture recognition accuracy based on Hu moment features, a new recognition algorithm was developed based on the fingertip structure detection. Firstly, the geometric features, the areas of skin region and the image, were designed to segment the skin region from the background in space of hue, saturation and value of brightness. Secondly, the cam point inspections were carried out and the fingertip was detected after the contour approximation. After that, the 7-dimensional feature vector was built. Finally, the distance marching criterion was utilized to recognize the hand gesture. Compared with the Hu moment feature recognition, the developed recognition algorithm improved the recognition accuracy by 2.7%.

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Human–Computer Interaction for Smart Environment Applications Using Fuzzy Hand Posture and Gesture Models

Cited by 68 publications

References 8 publications

Fuzzy human motion analysis: A review

Fuzzy human motion analysis: A review

On-Road Sensor Configuration Design for Traffic Flow Prediction Using Fuzzy Neural Networks and Taguchi Method

Hand Gesture Recognition Based on Fingertip Detection

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