Compression of Surface Texture Acceleration Signal Based on Spectrum Characteristics
Background: Adequate-data collection could enhance the realism of surface texture haptic online-rendering or offline-playback. A parallel challenge is how to reduce communication delays and improve storage space utilization. Methods: Based on the similarity of the short-term amplitude spectrumtrend,...
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Published in | Virtual Reality & Intelligent Hardware Vol. 5; no. 2; pp. 110 - 123 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
KeAi Communications Co., Ltd
01.04.2023
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Subjects | |
Online Access | Get full text |
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Summary: | Background: Adequate-data collection could enhance the realism of surface texture haptic online-rendering or offline-playback. A parallel challenge is how to reduce communication delays and improve storage space utilization. Methods: Based on the similarity of the short-term amplitude spectrumtrend, this paper proposes a frequency-domain compression method. A compression framework is designed, firstly to map the amplitude spectrum into a trend similarity grayscale image, compress it with the stillpicture-compression method, and then to adaptively encode the maximum amplitude and part of the initial phase of each time-window, achieving the final compression. Results: The comparison between the original signal and the recovered signal shows that when the time-frequency similarity is 90%, the average compression ratio of our method is 9.85% in the case of a single interact point. The subjective score for the similarity reached an excellent level, with an average score of 87.85. Conclusions: Our method can be used for offline compression of vibrotactile data. For the case of multi-interact points in space, the trend similarity grayscale image can be reused, and the compression ratio is further reduced. |
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ISSN: | 2096-5796 |
DOI: | 10.1016/j.vrih.2022.01.006 |