Interactive image selection for user annotation aided by the feature space projection
Interactive Learning of Visual Dictionaries Applied to Image Classification
Exploring visual analytics for supporting the user in active learning
| Full text | |
| Author(s): |
Bragantini, Jordao
;
Falcao, Alexandre X.
;
Najman, Laurent
Total Authors: 3
|
| Document type: | Journal article |
| Source: | PATTERN RECOGNITION; v. 131, p. 12-pg., 2022-07-13. |
| Abstract | |
Despite the progress of interactive image segmentation methods, high-quality pixel-level annotation is still time-consuming and laborious - a bottleneck for several deep learning applications. We take a step back to propose interactive and simultaneous segment annotation from multiple images guided by feature space projection. This strategy is in stark contrast to existing interactive segmentation methodologies, which perform annotation in the image domain. We show that feature space annotation achieves com-petitive results with state-of-the-art methods in foreground segmentation datasets: iCoSeg, DAVIS, and Rooftop. Moreover, in the semantic segmentation context, it achieves 91.5% accuracy in the Cityscapes dataset, being 74.75 times faster than the original annotation procedure. Further, our contribution sheds light on a novel direction for interactive image annotation that can be integrated with existing method-ologies. The supplementary material presents video demonstrations. Code available at https://github.com/ LIDS- UNICAMP/rethinking- interactive- image-segmentation . (c) 2022 Elsevier Ltd. All rights reserved. (AU) | |
| FAPESP's process: | 19/21734-9 - Interactive co-segmentation with projection learning |
| Grantee: | Jordão Okuma Barbosa Ferraz Bragantini |
| Support Opportunities: | Scholarships abroad - Research Internship - Scientific Initiation |
| FAPESP's process: | 14/12236-1 - AnImaLS: Annotation of Images in Large Scale: what can machines and specialists learn from interaction? |
| Grantee: | Alexandre Xavier Falcão |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 19/11349-0 - Image segmentation based on dynamic trees and neural networks |
| Grantee: | Jordão Okuma Barbosa Ferraz Bragantini |
| Support Opportunities: | Scholarships in Brazil - Scientific Initiation |