Independent pathfinding with collision avoidance for visually impaired individuals.

ABSTRACT: Computer vision tasks such as image segmentation, object detection, and face recognition have been crucial in developing assistance systems for visually impaired individuals. Among these, image segmentation plays a vital role in helping them navigate safely. However, this task is more complex as it requires detailed spatial information. In this article, we propose a novel panoptic segmentation framework that serves as the foundation for an effective pathfinding system, combining robust collision avoidance with high performance. Our contribution includes a single-stage instance segmentation method built on a ResNet101-FPN encoder-decoder architecture. Additionally, we created a customized panoptic labeled dataset to meet the specific needs of visually impaired individuals, aiming to support

SUBMITTER: Ghahremanians T 

PROVIDER: S-EPMC12514152 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature