mlsanityData to 14 Oct 2026

High-Quality, ROS Compatible Video Encoding and Decoding for High-Definition Datasets

arXiv 2408.00538 ↗First posted 1 Aug 2024cs.RO cs.CVcited by 0

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Abstract (arXiv)

Robotic datasets are important for scientific benchmarking and developing algorithms, for example for Simultaneous Localization and Mapping (SLAM). Modern robotic datasets feature video data of high resolution and high framerates. Storing and sharing those datasets becomes thus very costly, especially if more than one camera is used for the datasets. It is thus essential to store this video data in a compressed format. This paper investigates the use of modern video encoders for robotic datasets. We provide a software that can replay mp4 videos within ROS 1 and ROS 2 frameworks, supporting the synchronized playback in simulated time. Furthermore, the paper evaluates different encoders and their settings to find optimal configurations in terms of resulting size, quality and encoding time. Through this work we show that it is possible to store and share even highest quality video datasets within reasonable storage constraints.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 7 of its 27 references that are in the map. First posted on arXiv 1 Aug 2024.

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7 of 27 references.

References · 7

  1. 2016Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Agecited by 411
  2. 2020A Technical Overview of AV1cited by 47
  3. 2020Advanced Mapping Robot and High-Resolution Datasetcited by 3
  4. 2023The SLAM Hive Benchmarking Suitecited by 2
  5. 2024ShanghaiTech Mapping Robot is All You Need: Robot System for Collecting Universal Ground Vehicle Datasetscited by 2
  6. 2024Benchmarking SLAM Algorithms in the Cloud: The SLAM Hive Benchmarking Suitecited by 2
  7. 2022Cluster on Wheelscited by 1

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