Feasibility Study of Multi-Layer VVC Coding Scheme for Hybrid Machine-Human Consumption
Laitinen, Jaakko; Partanen, Tero; Mercat, Alexandre; Vanne, Jarno; Hannuksela, Miska; Zhang, Honglei; Aminlou, Alireza; Cricri, Francesco (2024-07)
Laitinen, Jaakko
Partanen, Tero
Mercat, Alexandre
Vanne, Jarno
Hannuksela, Miska
Zhang, Honglei
Aminlou, Alireza
Cricri, Francesco
IEEE
07 / 2024
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202410309688
https://urn.fi/URN:NBN:fi:tuni-202410309688
Kuvaus
Peer reviewed
Tiivistelmä
The proliferation of machine vision applications necessitates developing more efficient visual data compression schemes for machine consumption. However, numerous automated use cases still require keeping humans in the loop, leading to the need for a machine-optimized video streaming with the option for human supervision. This paper investigates the feasibility of using the multi-layer coding approach of the emerging Versatile Video Coding (VVC) standard to create favorable conditions for hybrid machine-human consumption. We introduce a multi-layer coding scheme, where the base layer (BL) is optimized for machines and the enhancement layer (EL) complements the stream for human vision. Our results demonstrate that the bitrate of the proposed multi-layer stream (BL + EL) is, on average, 11% higher than that of a single-layer VVC. However, the more compact BL yields overall bandwidth savings as long as the EL is required less than 80% of the time.
Kokoelmat
- TUNICRIS-julkaisut [18911]