Shape polygonization is an effective and convenient method to compress the storage requirements of a shape curve. Polygonal approximation offers an invariant representation of local properties even after digitization of a shape curve. In this paper, we propose to use universal threshold for polygonal approximation of any two-dimensional object boundary by exploiting the strength of small eigenvalues. We also propose to adapt the Jaccard Index as a metric to measure the effectiveness of shape polygonization. In the context of this paper, we have conducted extensive experiments on the semantically segmented images from Cityscapes dataset to polygonize the objects in the traffic scenes. Further, to corroborate the efficacy of the proposed method, experiments on the MPEG-7 shape database are conducted. Results obtained by the proposed technique are encouraging and can enable greater compression of annotation documents. This is particularly critical in the domain of instrumented vehicles where large volumes of high quality video must be exhaustively annotated without loss of accuracy and least man-hours.
Metadata
Item Type:
Conference or Workshop Item (Paper)
Event Type:
Conference
Refereed:
Yes
Additional Information:
pp 77- 84
Uncontrolled Keywords:
Dominant Point; Shape Representation; Shape polygonization; Small Eigenvalue
This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:
European Research Council (ERC) under the European Union’s Hori-zon 2020 research and innovation programme (grant agreement number 688099) projectC l oud−LSV Aandfrom Science Foundation Ireland under grant numberSF I/16/SP/3804.
ID Code:
24881
Deposited On:
31 Aug 2020 11:50 by
Venkatesh Gurram Munirathnam
. Last Modified 05 Jan 2022 17:04