APSIPA Transactions on Signal and Information Processing > Vol 4 > Issue 1

Mesh-based piecewise planar motion compensation and optical flow clustering for ROI coding

Holger Meuel, Gottfried Wilhelm Leibniz Universität Hannover, Germany, meuel@tnt.uni-hannover.de , Marco Munderloh, Gottfried Wilhelm Leibniz Universität Hannover, Germany, Matthias Reso, Gottfried Wilhelm Leibniz Universität Hannover, Germany, Jörn Ostermann, Gottfried Wilhelm Leibniz Universität Hannover, Germany
 
Suggested Citation
Holger Meuel, Marco Munderloh, Matthias Reso and Jörn Ostermann (2015), "Mesh-based piecewise planar motion compensation and optical flow clustering for ROI coding", APSIPA Transactions on Signal and Information Processing: Vol. 4: No. 1, e13. http://dx.doi.org/10.1017/ATSIP.2015.12

Publication Date: 02 Oct 2015
© 2015 Holger Meuel, Marco Munderloh, Matthias Reso and Jörn Ostermann
 
Subjects
 
Keywords
Region of interest ROI codingMesh-based motion compensationSuperpixel segmentationLow bit rate HDTV video codingMoving object detection
 

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In this article:
I. INTRODUCTION IN REGION OF INTEREST (ROI) CODING 
II. OVERVIEW OF THE PROPOSED ROI CODING SYSTEM FOR AERIAL SURVEILLANCE VIDEO 
III. SUPERPIXEL-SEGMENTATION 
IV. REDUCTION OF FP DETECTIONS OF MOS BY MESH-BASED MOTION COMPENSATION AND CLUSTER FILTERING 
V. EXPERIMENTS 
VI. CONCLUSIONS 

Abstract

For the transmission of aerial surveillance videos taken from unmanned aerial vehicles (UAVs), region of interest (ROI)-based coding systems are of growing interest in order to cope with the limited channel capacities available. We present a fully automatic detection and coding system which is capable of transmitting high-resolution aerial surveillance videos at very low bit rates. Our coding system is based on the transmission of ROI areas only. We assume two different kinds of ROIs: in order to limit the transmission bit rate while simultaneously retaining a high-quality view of the ground, we only transmit new emerging areas (ROI-NA) for each frame instead of the entire frame. At the decoder side, the surface of the earth is reconstructed from transmitted ROI-NA by means of global motion compensation (GMC). In order to retain the movement of moving objects not conforming with the motion of the ground (like moving cars and their previously occluded ground), we additionally consider regions containing such objects as interesting (ROI-MO). Finally, both ROIs are used as input to an externally controlled video encoder. While we use GMC for the reconstruction of the ground from ROI-NA, we use meshed-based motion compensation in order to generate the pelwise difference in the luminance channel (difference image) between the mesh-based motion compensated and the current input image to detect the ROI-MO. High spots of energy within this difference image are used as seeds to select corresponding superpixels from an independent (temporally consistent) superpixel segmentation of the input image in order to obtain accurate shape information of ROI-MO. For a false positive detection rate (regions falsely classified as containing local motion) of less than 2% we detect more than 97% true positives (correctly detected ROI-MOs) in challenging scenarios. Furthermore, we propose to use a modified high-efficiency video coding (HEVC) video encoder. Retaining full HDTV video resolution at 30 fps and subjectively high quality we achieve bit rates of about 0.6–0.9 Mbit/s, which is a bit rate saving of about 90% compared to an unmodified HEVC encoder.

DOI:10.1017/ATSIP.2015.12