Superpixel-based segmentation of moving objects for low bitrate ROI coding systems

A major constraint for mobile surveillance systems (e.g. UAV-mounted) is the limited available bandwidth. Thus, ROI-based video coding, where only important image parts are transmitted with high data rate, seems to be a suitable solution for these applications. The challenging part in these systems is to reliably detect the regions of interest (ROI) and to select the corresponding macroblocks to be encoded in high quality. Recently, difference image-based moving object detectors have been used for this purpose. But as these pixel-based approaches fail for homogeneous parts of moving objects, which leads to artifacts in the decoded video stream, this paper proposes the use of a superpixel-based macroblock selection. It is shown that the proposed approach significantly reduces artifacts by raising the moving objects detection rate from 7 % to over 96 % while increasing the data rate by only 20% to 1.5-4 ^Mbit/s (full HD resolution, 30 Hz) still meeting the given constraints. Moreover, other simple approaches (dilation) as well as state-of-the-art GraphCut-based approaches are outperformed.