Compact Visual Data Representation for Green Multimedia -- A Human Visual System Perspective
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866909440798621696 |
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| author | Chen, Peilin Fang, Xiaohan Wang, Meng Wang, Shiqi Ma, Siwei |
| author_facet | Chen, Peilin Fang, Xiaohan Wang, Meng Wang, Shiqi Ma, Siwei |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_14135 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Compact Visual Data Representation for Green Multimedia -- A Human Visual System Perspective Chen, Peilin Fang, Xiaohan Wang, Meng Wang, Shiqi Ma, Siwei Image and Video Processing Multimedia 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. |
| title | Compact Visual Data Representation for Green Multimedia -- A Human Visual System Perspective |
| topic | Image and Video Processing Multimedia |
| url | https://arxiv.org/abs/2411.14135 |