Implementation of gesture driven virtual reality for car racing game using back propagation neural network

Saha, Sriparna; Lahiri, Rimita; Konar, Amit; Ralescu, Anca; Nagar, Atulya K.

doi:10.1109/ssci.2017.8280839

Cited by 2 publications

(4 citation statements)

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“…The main contribution of this work lies in its efficiency and applicability towards optimized training in neural network. Although this method is an improvement of [14], a high level precision is obtained. Employing this gesture based car driving, a number of degrees of freedom can be enjoyed by the gamer.…”

Section: Discussionmentioning

confidence: 99%

“…LM-NN outperforms other training methods of neural network in terms of sensitivity and specificity. Further in this work, a reduced number of features compared to [14] have been used for virtual implementation of car gaming system. The proposed work has redefined the significance of Kinect sensor for modern day gaming interfaces.…”

Section: Discussionmentioning

confidence: 99%

“…Two angular features are extracted from the driving gesture, obtained from the skeleton image of the player, are given as αL = angle (SC, HC, HaL) (13) αR = angle (SC, HC, HaR) (14) where, αL is the angle between SC, HC and HaL, and αR is the angle between SC, HC and HaR. For straight driving, αL ≈ αR.…”

Section: A Determination Of Steering Directionmentioning

confidence: 99%

“…The proposed work is an improvement of previous work [14], where the back-propagation neural network with steepest descent technique is used for weight adaptation. The convergence speed of steepest descent training algorithm is very slow due to its small step size.…”

Section: Introductionmentioning

confidence: 99%

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Gesture based Virtual Reality Implementation for Car Racing Game employing an Improved Neural Network

Ganguly¹,

Vishwakarma²,

Rahul³

et al. 2019

IJERT

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This paper explores the formation of a smart human-computer interfacing system for computer gaming using Microsoft's Kinect sensor. Gesture based monitoring is chosen as the most prominent modality to continue the car racing game. Angle based features are extracted from skeletal images obtained from the sensor. Levenberg-Marquardt optimization technique is used for weight adaptation for a feed-forward neural network using back-propagation learning algorithm. A gesture based console for Asphalt 8: Airborne game is implemented. Experimental results reveal that the proposed method outperforms the state-of-the-art training methods of neural network.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: A Determination Of Steering Directionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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