An Interactive Approach to Pose-Assisted and Appearance-Based Segmentation of Humans
Abstract
An interactive human segmentation approach is described. Given regions of interest provided by users, the approach iteratively estimates segmentation via a generalized EM algorithm. Specifically, it encodes both spatial and color information in a nonparametric kernel density estimator, and incorporates local MRF constraints and global pose inferences to propagate beliefs over image space iteratively to determine a coherent segmentation. This ensures the segmented humans resemble the shapes of human poses. Additionally, a layered occlusion model and a probabilistic occlusion reasoning method are proposed to handle segmentation of multiple humans in occlusion. The approach is tested on a wide variety of images containing single or multiple occluded humans, and the segmentation performance is evaluated quantitatively.
Cite
Text
Lin et al. "An Interactive Approach to Pose-Assisted and Appearance-Based Segmentation of Humans." IEEE/CVF International Conference on Computer Vision, 2007. doi:10.1109/ICCV.2007.4409123Markdown
[Lin et al. "An Interactive Approach to Pose-Assisted and Appearance-Based Segmentation of Humans." IEEE/CVF International Conference on Computer Vision, 2007.](https://mlanthology.org/iccv/2007/lin2007iccv-interactive/) doi:10.1109/ICCV.2007.4409123BibTeX
@inproceedings{lin2007iccv-interactive,
title = {{An Interactive Approach to Pose-Assisted and Appearance-Based Segmentation of Humans}},
author = {Lin, Zhe and Davis, Larry S. and Doermann, David S. and DeMenthon, Daniel},
booktitle = {IEEE/CVF International Conference on Computer Vision},
year = {2007},
pages = {1-8},
doi = {10.1109/ICCV.2007.4409123},
url = {https://mlanthology.org/iccv/2007/lin2007iccv-interactive/}
}