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Paper

Spatio-Temporal Image Boundary Extrapolation

MPS-Authors

Bhattacharyya,  Apratim
Computer Vision and Multimodal Computing, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons44976

Malinowski,  Mateusz
Computer Vision and Multimodal Computing, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons44451

Fritz,  Mario
Computer Vision and Multimodal Computing, MPI for Informatics, Max Planck Society;

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Fulltext (public)

arXiv:1605.07363.pdf
(Preprint), 2MB

Supplementary Material (public)
There is no public supplementary material available
Citation

Bhattacharyya, A., Malinowski, M., & Fritz, M. (2016). Spatio-Temporal Image Boundary Extrapolation. Retrieved from http://arxiv.org/abs/1605.07363.


Cite as: http://hdl.handle.net/11858/00-001M-0000-002B-065A-1
Abstract
Boundary prediction in images as well as video has been a very active topic of research and organizing visual information into boundaries and segments is believed to be a corner stone of visual perception. While prior work has focused on predicting boundaries for observed frames, our work aims at predicting boundaries of future unobserved frames. This requires our model to learn about the fate of boundaries and extrapolate motion patterns. We experiment on established real-world video segmentation dataset, which provides a testbed for this new task. We show for the first time spatio-temporal boundary extrapolation in this challenging scenario. Furthermore, we show long-term prediction of boundaries in situations where the motion is governed by the laws of physics. We successfully predict boundaries in a billiard scenario without any assumptions of a strong parametric model or any object notion. We argue that our model has with minimalistic model assumptions derived a notion of 'intuitive physics' that can be applied to novel scenes.