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Increasing Hand Gesture Recognition Robustness for Real-Time Movements with the Kinect Method

S.Chandrasekhar .

Abstract


Hand movement affirmation is an essential point in human-PC cooperation. In any case, an enormous piece of the ongoing techniques are obfuscated and drawn-out, which compels the usage of hand movement affirmation dynamically conditions. In this paper, we propose a data mix based hand movement affirmation exhibit by merging significance information and skeleton data. Considering the specific division and following with Kinect V2, the model can achieve continuous execution, which is 18.7% speedier than a piece of the top tier procedures. Considering the preliminary occurs, the proposed model is precise and enthusiastic to insurgency, flip, scale changes, lighting changes, confused establishment, and twists. This ensures its usage in different authentic human-PC participation tasks.


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References


Zhou, H. (2003, October). Tracking articulated hand motion with eigen dynamics analysis. In Proceedings Ninth IEEE International Conference on Computer Vision (pp. 1102-1109). IEEE.

Lee, J., & Kunii, T. L. (1993). Constraint-based hand animation. In Models and techniques in computer animation (pp. 110-127). Springer Japan.

Rehg, J. M., & Kanade, T. (1994). Visual tracking of high dof articulated structures: an application to human hand tracking. In Computer Vision—ECCV'94: Third European Conference on Computer Vision Stockholm, Sweden, May 2–6 1994 Proceedings, Volume II 3 (pp. 35-46). Springer Berlin Heidelberg.

Erol, A., Bebis, G., Nicolescu, M., Boyle, R. D., & Twombly, X. (2007). Vision-based hand pose estimation: A review. Computer Vision and Image Understanding, 108(1-2), 52-73.

Howse, J. (2013). OpenCV computer vision with python (Vol. 27). Birmingham, UK: Packt Publishing.

Stenger, B., Thayananthan, A., Torr, P. H., & Cipolla, R. (2006). Model-based hand tracking using a hierarchical bayesian filter. IEEE transactions on pattern analysis and machine intelligence, 28(9), 1372-1384.

Cui, J., & Sun, Z. (2004). Model-based visual hand posture tracking for guiding a dexterous robotic hand. Optics communications, 235(4-6), 311-318.

Bray, M., Koller-Meier, E., & Van Gool, L. (2004, May). Smart particle filtering for 3D hand tracking. In Sixth IEEE International Conference on Automatic Face and Gesture Recognition, 2004. Proceedings. (pp. 675-680). IEEE.

de La Gorce, M., Paragios, N., & Fleet, D. J. (2008, June). Model-based hand tracking with texture, shading and self-occlusions. In 2008 IEEE Conference on Computer Vision and Pattern Recognition (pp. 1-8). IEEE.

Malassiotis, S., Tsalakanidou, F., Mavridis, N., Giagourta, V., Grammalidis, N., & Strintzis, M. G. (2001, October). A face and gesture recognition system based on an active stereo sensor. In Proceedings 2001 International Conference on Image Processing (Cat. No. 01CH37205) (Vol. 3, pp. 955-958). IEEE.


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