  In recent years, video data has dominated internet traffic and becomes one of
the major data formats. With the emerging 5G and internet of things (IoT)
technologies, more and more videos are generated by edge devices, sent across
networks, and consumed by machines. The volume of video consumed by machine is
exceeding the volume of video consumed by humans. Machine vision tasks include
object detection, segmentation, tracking, and other machine-based applications,
which are quite different from those for human consumption. On the other hand,
due to large volumes of video data, it is essential to compress video before
transmission. Thus, efficient video coding for machines (VCM) has become an
important topic in academia and industry. In July 2019, the international
standardization organization, i.e., MPEG, created an Ad-Hoc group named VCM to
study the requirements for potential standardization work. In this paper, we
will address the recent development activities in the MPEG VCM group.
Specifically, we will first provide an overview of the MPEG VCM group including
use cases, requirements, processing pipelines, plan for potential VCM
standards, followed by the evaluation framework including machine-vision tasks,
dataset, evaluation metrics, and anchor generation. We then introduce
technology solutions proposed so far and discuss the recent responses to the
Call for Evidence issued by MPEG VCM group.
