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U-RME: Underwater Refined Motion Estimation in Hazy, Cluttered and Dynamic Environments
S. Gupta, P. Mukherjee, , B. Lall
Published in Springer Science and Business Media Deutschland GmbH
Volume: 1249
Pages: 198 - 208
Optical Flow is a popular method of computer vision for motion estimation. In this paper, we present a refined optical flow estimation method. Central to our approach is exploiting contour information as most of the motion lies on the edges. Further, we have formulated it as sparse to dense motion estimation. Proposed method has been evaluated on challenging real life image sequences of KITTI and Fish4Knowledge database. Results demonstrate that method performs well in case of low contrast, highly cluttered background, dynamic background, occlusion and illumination change. © 2020, Springer Nature Singapore Pte Ltd.
About the journal
JournalData powered by TypesetCommunications in Computer and Information Science
PublisherData powered by TypesetSpringer Science and Business Media Deutschland GmbH