¹School of Computer Science and Technology, Shandong University, Jinan, China
²School of Computer Science and Technology, Shandong University of Finance and Economics, Jinan, China

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Abstract—In this paper, a new haptic data compression algorithm is presented. The algorithm partitions haptic data samples into subsets based on knowledge from human haptic perception. To reduce the number of data subsets, a prediction model based on a tangential direction concept is derived that adapts to local geometric changes of haptic signals. Furthermore, to improve signal approximation precision, each haptic data subset is fitted by a quadratic curve. Accordingly, only the coefficients of the quadratic curves are encoded. Experiments are performed on datasets acquired using a six-degrees-of-freedom haptic-enabled telepresence system. The experimental results demonstrate that the proposed haptic data compression algorithm can potentially outperform existed methods in the literature.

Index Terms—haptics, linear prediction, compression, curve reconstruction

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Cite: Fenghua Guo, Caiming Zhang, Yan He, "Haptic Data Compression Based on a Linear Prediction Model and Quadratic Curve Reconstruction," Journal of Software vol. 9, no. 11, pp. 2796-2803, 2014.