Perceptual and Bitrate-Scalable Coding of Haptic Surface Texture Signals

• Published in: IEEE journal of selected topics in signal processing Vol. 9; no. 3; pp. 462 - 473
• Main Authors: Chaudhari, Rahul, Schuwerk, Clemens, Danaei, Mojtaba, Steinbach, Eckehard
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.04.2015; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Bit rate; Codec; Codecs; Coding; Data compression; Haptic interfaces; haptic textures; Haptics; Masking; Media; Noise; Noise levels; perceptual coding; Speech coding; Surface layer; Surface texture; Texture
• ISSN: 1932-4553; 1941-0484
• DOI: 10.1109/JSTSP.2014.2374574

Applications involving indirect interpersonal communication, such as collaborative design/assembly/exploration of physical objects, can benefit strongly from the transmission of contact-based haptic media, in addition to the more traditional audiovisual media. Inclusion of haptic media has been shown to improve immersiveness, task performance, and the overall experience of task execution. While several decades of research have been dedicated to the acquisition, processing, coding, and display of audio and video streams, similar aspects for haptic streams have been addressed only recently. Simultaneous masking is a perceptual phenomenon widely exploited in the compression of audio data. In the first part of this paper, to the best of our knowledge, we present first-time empirical evidence for masking in the perception of wideband vibrotactile signals. Our results show that this phenomenon for haptics is very similar to its auditory analog. Signals closer in frequency to a powerful masker ( 25 dB above detection threshold) are masked more strongly (peak threshold-shifts of up to 28 dB) than those away from the masker (threshold-shifts of 15-20 dB). The masking curves approximately follow the masker's spectral profile. In the second part of this paper, we present a bitrate scalable haptic texture codec, which incorporates the masking model and describe its subjective and objective performance evaluation. Experiments show that we can drive down the codec output bitrate to a very low value of 2.3 kbps, without the subjects being able to reliable discriminate between the codec input and distorted output texture signals.