Authors:
James McCullough
1
;
Naseer Al-Jawad
1
and
Tuan Nguyen
2
Affiliations:
1
School of Computing, University of Buckingham, Hunter Street, Buckingham, U.K.
;
2
School of Computing & Mathematical Sciences, University of Greenwich, Old Royal Naval College, Park Row, London, U.K.
Keyword(s):
Video Compression, Optical Flow, Physics, Mechanics, Acceleration, Velocity, Segmentation.
Abstract:
Optical flow is a fundamental component of video compression as it can be used to effectively compress sequential frames. However, currently optical flow is only a transformation of one frame into another. This paper considers the possibility of representing optical flow based on physics principles which has not, to our knowledge, been researched before. Video often consists of real-world events captured by a camera, meaning that objects within videos follow Newtonian physics, so the video can be compressed by converting the motion of the object into physics-based motion paths. The proposed algorithm converts an object’s location over a series of frames into a sequence of physics motion paths. The space cost in saving these motion paths could be considerably smaller compared with traditional optical flow, and this improves video compression in exchange for increased encoding/decoding times. Based on our experimental implementation, motion paths can be used to compress the motion of o
bjects on basic trajectories. By comparing the file sizes between original and processed image sequences, effective compression on basic object movements can be identified.
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