Integration of Bottom-up and Top-Down Cues for Visual Attention Using Non-Linear Relaxation
Abstract
Active and selective perception seeks regions of interest in an image in order to reduce the computational complexity associated with time-consuming processes such as object recognition. We describe in this paper a visual attention system that extracts regions of interest by integrating multiple image cues. Bottom-up cues are detected by decomposing the image into a number: of feature and conspicuity maps, while a-priori knowledge (i.e. models) about objects is used to generate top-down attention cues. Bottom-up and top-down information is combined through a non-linear relaxation process using energy minimization-like procedures. The functionality of the attention system is expanded by the introduction of an alerting (motion-based) system able to explore and avoid obstacles. Experimental results are reported, using cluttered and noisy scenes.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Cite
Text
Milanese et al. "Integration of Bottom-up and Top-Down Cues for Visual Attention Using Non-Linear Relaxation." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1994. doi:10.1109/CVPR.1994.323898Markdown
[Milanese et al. "Integration of Bottom-up and Top-Down Cues for Visual Attention Using Non-Linear Relaxation." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1994.](https://mlanthology.org/cvpr/1994/milanese1994cvpr-integration/) doi:10.1109/CVPR.1994.323898BibTeX
@inproceedings{milanese1994cvpr-integration,
title = {{Integration of Bottom-up and Top-Down Cues for Visual Attention Using Non-Linear Relaxation}},
author = {Milanese, Ruggero and Wechsler, Harry and Gil, Sylvia and Bost, Jean-Marc and Pun, Thierry},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {1994},
pages = {781-785},
doi = {10.1109/CVPR.1994.323898},
url = {https://mlanthology.org/cvpr/1994/milanese1994cvpr-integration/}
}