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Improving spatial codification in semantic segmentation

Ventura, Carles, Giró-i-Nieto, Xavier orcid logoORCID: 0000-0002-9935-5332, Vilaplana, Veronica, McGuinness, Kevin orcid logoORCID: 0000-0003-1336-6477, Marqués, Ferran and O'Connor, Noel E. orcid logoORCID: 0000-0002-4033-9135 (2015) Improving spatial codification in semantic segmentation. In: IEEE Intl Conference on Image Processing, 27-30 Sep 2015, Quebec City, Canada.

Abstract
This paper explores novel approaches for improving the spatial codification for the pooling of local descriptors to solve the semantic segmentation problem. We propose to partition the image into three regions for each object to be described: Figure, Border and Ground. This partition aims at minimizing the influence of the image context on the object description and vice versa by introducing an intermediate zone around the object contour. Furthermore, we also propose a richer visual descriptor of the object by applying a Spatial Pyramid over the Figure region. Two novel Spatial Pyramid configurations are explored: Cartesian-based and crown-based Spatial Pyramids. We test these approaches with state-of-the-art techniques and show that they improve the Figure-Ground based pooling in the Pascal VOC 2011 and 2012 semantic segmentation challenges.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:Semantic segmentation; Object recognition; Object segmentation; Spatial codification
Subjects:Computer Science > Image processing
DCU Faculties and Centres:Research Initiatives and Centres > INSIGHT Centre for Data Analytics
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland
ID Code:20581
Deposited On:07 Oct 2015 12:52 by Noel Edward O'connor . Last Modified 24 Jan 2019 15:52
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