The alpha parallelogram predictor: A lossless compression method for motion capture data

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Title: The alpha parallelogram predictor: A lossless compression method for motion capture data

Authors: Pengjie Wang , Zhigeng Pan d,a , Mingmin Zhang a, , Rynson WH Lau c , Haiyu Song

Abstract: Motion capture data in an uncompressed form can be expensive to store, and slow to load and transmit. Current compression methods for motion capture data are primarily lossy and cause distortions in the motion data. In this paper, we present a lossless compression algorithm for motion capture data. First, we propose a novel Alpha Parallelogram Predictor (APP) to estimate the DOF (degree of freedom) of each child joint from those of its immediate neighbors and parents that have already been processed. The prediction parameter of the predictor, which is referred to as the alpha parameter, is adaptively chosen from a care- fully designed lookup table. Second, we divide the predicted and actual values into three components: sign, exponent and mantissa. We then compress their corrections separately with context-based arithmetic coding. Compared with other lossless compression methods, our approach can achieve a higher compression ratio with a comparable compression time. It can be used in situations where lossy compression is not preferred.   

Publish Year: 2013

Published in: Information Sciences - Science Direct

Number of Pages: 10

موضوع: فشرده سازی داده ها

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