High-Quality, ROS Compatible Video Encoding and Decoding for High-Definition Datasets
This work addresses storage and sharing challenges for robotic researchers using high-definition video datasets, but it is incremental as it applies existing video encoding methods to a specific domain.
The paper tackles the problem of high storage costs for high-resolution robotic video datasets by evaluating modern video encoders and providing ROS-compatible software for compressed video playback, showing that high-quality datasets can be stored within reasonable constraints.
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.