Projects per year
Abstract
Dense motion estimation for dynamic natural phenomena (water, smoke, fire, etc.) is a significant open problem. Current approaches tend to be either general, giving poor results, or specialise in one phenomenon and fail to generalise. Segmentation of phenomena is also an open problem. This paper describes an approach to estimate dense motion for dynamic phenomena that is simple, general, and which yields state of the art results. We use our dense motion field to segment phenomena to above state of the art levels. We demonstrate our contributions using lab-based video, video from a public dataset, and from the internet.
Original language | English |
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Publication status | Published - 4 Sept 2018 |
Event | 29th British Machine Vision Conference, BMVC 2018 - Northumbria University, Newcastle, UK United Kingdom Duration: 3 Sept 2018 → 6 Sept 2018 http://bmvc2018.org/ |
Conference
Conference | 29th British Machine Vision Conference, BMVC 2018 |
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Abbreviated title | BMVC 2018 |
Country/Territory | UK United Kingdom |
City | Newcastle |
Period | 3/09/18 → 6/09/18 |
Internet address |
Keywords
- natutal phenomena, tracking, segmentation
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Dive into the research topics of 'Motion Estimation and Segmentation of Natural Phenomena'. Together they form a unique fingerprint.Projects
- 1 Finished
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Centre for the Analysis of Motion, Entertainment Research and Applications (CAMERA)
Cosker, D. (PI), Bilzon, J. (CoI), Campbell, N. (CoI), Cazzola, D. (CoI), Colyer, S. (CoI), Fincham Haines, T. (CoI), Hall, P. (CoI), Kim, K. I. (CoI), Lutteroth, C. (CoI), McGuigan, P. (CoI), O'Neill, E. (CoI), Richardt, C. (CoI), Salo, A. (CoI), Seminati, E. (CoI), Tabor, A. (CoI) & Yang, Y. (CoI)
Engineering and Physical Sciences Research Council
1/09/15 → 28/02/21
Project: Research council