Adaptive Spatial Re-sampling Method for Video Coding for Machines

Eun-bin An, Ayoung Kim, Soon-Heung Jung, Hyon-Gon Choo, Kwang-deok Seo

Abstract: As the performance of machine vision continues to improve, it is being used in various industrial fields to analyze and generate massive amounts of video data. Although the demand for and consumption of video data by machines has increased significantly, video coding for machines needs to be improved. Spatial re-sampling plays a critical role in video coding for machines because it reduces the volume of the video data to be processed while maintaining the shape of the data’s features that are important for the machine to reference when processing the video. An effective method of determining the intensity of spatial resampling as an efficient coding tool for machines is still in the early stages. Here, we propose a method of determining an optimal scale factor for spatial re-sampling by collecting and analyzing information on the number of objects and the ratio of the area occupied by the object within a picture.

External IDs:dblp:conf/apsipa/AnKJCS24