Compression of Surface Texture Acceleration Signal Based on Spectrum Characteristics

Abstract

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.