From Event: SPIE Optical Engineering + Applications, 2016
Perspective motion is commonly represented in video content that is captured and compressed for various applications
including cloud gaming, vehicle and aerial monitoring, etc. Existing approaches based on an eight-parameter
homography motion model cannot deal with this efficiently, either due to low prediction accuracy or excessive
bit rate overhead. In this paper, we consider the camera motion model and scene structure in such video content
and propose a joint global and local homography motion coding approach for video with perspective motion.
The camera motion is estimated by a computer vision approach, and camera intrinsic and extrinsic parameters
are globally coded at the frame level. The scene is modeled as piece-wise planes, and three plane parameters
are coded at the block level. Fast gradient-based approaches are employed to search for the plane parameters
for each block region. In this way, improved prediction accuracy and low bit costs are achieved. Experimental
results based on the HEVC test model show that up to 9.1% bit rate savings can be achieved (with equal PSNR
quality) on test video content with perspective motion. Test sequences for the example applications showed a
bit rate savings ranging from 3.7 to 9.1%.
Xiulian Peng, Jizheng Xu, and Gary J. Sullivan, "Scene-aware joint global and local homographic video coding," Proc. SPIE 9971, Applications of Digital Image Processing XXXIX, 99711J (Presented at SPIE Optical Engineering + Applications: August 31, 2016; Published: 27 September 2016); https://doi.org/10.1117/12.2240141.
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