Video coding for machines using region-of-interest-based retargeting.

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Bibliographic Details
Title: Video coding for machines using region-of-interest-based retargeting.
Authors: Różek, Sławomir1 (AUTHOR), Stankiewicz, Olgierd1 (AUTHOR) olgierd.stankiewicz@put.poznan.pl, Maćkowiak, Sławomir1 (AUTHOR), Grajek, Tomasz1 (AUTHOR), Stankowski, Jakub1 (AUTHOR), Wawrzyniak, Maciej1 (AUTHOR), Lorkiewicz, Mateusz1 (AUTHOR), Ding, Ding2 (AUTHOR), Liu, Shan2 (AUTHOR), Domański, Marek1 (AUTHOR)
Source: EURASIP Journal on Image & Video Processing. 10/24/2025, Vol. 2025 Issue 1, p1-17. 17p.
Subjects: Video compression, Video coding, Video processing, MPEG (Video coding standard), Computer vision, Object recognition (Computer vision)
Abstract: The work is focused on video compression for the scenarios, where the decoded video serves not only human viewers but also as input for systems implementing various machine vision tasks, such as object detection and tracking. The proposed innovative tool is based on retargeting video frames processed based on Regions of Interest (RoI), corresponding to the individual objects detected in the frames. Experimental evaluation demonstrates significant average bitrate reduction while maintaining the same quality, ranging from 3 to 57% depending on the machine vision task and encoding scenario. The proposal underwent thorough consideration within the MPEG group and was adopted for the upcoming Video Coding for Machines (VCM) technology. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
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Abstract:The work is focused on video compression for the scenarios, where the decoded video serves not only human viewers but also as input for systems implementing various machine vision tasks, such as object detection and tracking. The proposed innovative tool is based on retargeting video frames processed based on Regions of Interest (RoI), corresponding to the individual objects detected in the frames. Experimental evaluation demonstrates significant average bitrate reduction while maintaining the same quality, ranging from 3 to 57% depending on the machine vision task and encoding scenario. The proposal underwent thorough consideration within the MPEG group and was adopted for the upcoming Video Coding for Machines (VCM) technology. [ABSTRACT FROM AUTHOR]
ISSN:16875176
DOI:10.1186/s13640-025-00682-3