Compact Visual Data Representation for Green Multimedia–A Human Visual System Perspective

The Human Visual System (HVS), with its intricate sophistication, is capable of achieving ultra-compact information compression for visual signals. This remarkable ability is coupled with high generalization capability and energy efficiency. By contrast, the state-of-the-art Versatile Video Coding (VVC) standard achieves a compression ratio of around 1,000 times for raw visual data. This notable disparity motivates the research community to draw inspiration to effectively handle the immense volume of visual data in a green way. Therefore, this paper provides a survey of how visual data can be efficiently represented for green multimedia, in particular when the ultimate task is knowledge extraction instead of visual signal reconstruction. We introduce recent research efforts that promote green, sustainable, and efficient multimedia in this field. Moreover, we discuss how the deep understanding of the HVS can benefit the research community, and envision the development of future green multimedia technologies.

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Publication Details

Journal
IEEE Journal on Emerging and Selected Topics in Circuits and Systems
Published
2024-12-30
DOI
https://doi.org/10.1109/jetcas.2024.3524260
Primary Topic
Image Retrieval and Classification Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Compact Visual Data Representation for Green Multimedia–A Human Visual System Perspective

Siwei Ma, Meng Wang, Shiqi Wang, Peilin Chen et al.
IEEE Journal on Emerging and Selected Topics in Circuits and Systems
Image Retrieval and Classification Techniques
article

Compact Visual Data Representation for Green Multimedia–A Human Visual System Perspective

Siwei Ma, Meng Wang, Shiqi Wang, Peilin Chen, Xiaohan Fang
article en

Abstract

The Human Visual System (HVS), with its intricate sophistication, is capable of achieving ultra-compact information compression for visual signals. This remarkable ability is coupled with high generalization capability and energy efficiency. By contrast, the state-of-the-art Versatile Video Coding (VVC) standard achieves a compression ratio of around 1,000 times for raw visual data. This notable disparity motivates the research community to draw inspiration to effectively handle the immense volume of visual data in a green way. Therefore, this paper provides a survey of how visual data can be efficiently represented for green multimedia, in particular when the ultimate task is knowledge extraction instead of visual signal reconstruction. We introduce recent research efforts that promote green, sustainable, and efficient multimedia in this field. Moreover, we discuss how the deep understanding of the HVS can benefit the research community, and envision the development of future green multimedia technologies.

IEEE Journal on Emerging and Selected Topics in Circuits and SystemsVol. 15(1)
City University of Hong Kong (HK), Peking University (CN)
Openalex Percentile: Top 76%
Image Retrieval and Classification Techniques
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