Manuel Guerrero-Viu
Papers
1
Total Citations
8
H-Index
1
About
Manuel Guerrero-Viu is a researcher whose work sits at the intersection of computer vision, assistive technology, and autonomous navigation. His most recognized contribution focuses on developing intelligent visual systems capable of extracting meaningful spatial information from unstructured environments — most notably through floor detection and door recognition to aid visually impaired individuals. His 2020 paper, "Floor Extraction and Door Detection for Visually Impaired Guidance," which has garnered 8 citations, addresses a critical gap in existing navigation research: while many prior works concentrated narrowly on obstacle avoidance, Guerrero-Viu's approach provides a broader environmental understanding, enabling more holistic and reliable path planning. By leveraging computer vision techniques, his work bridges the needs of both assistive technology users and autonomous robotic systems, demonstrating the dual applicability of his methods. His research reflects a commitment to designing inclusive, real-world solutions that empower individuals with visual impairments to navigate unfamiliar spaces with greater confidence and safety. For students and researchers working in human-centered AI, robotics, or accessibility technology, Guerrero-Viu's contributions offer a compelling model of applied computer vision research with meaningful societal impact.
Research Focus
Key Achievements
Top Papers
- 1Floor Extraction and Door Detection for Visually Impaired Guidance8 citations · 2020
Key Collaborators
Related papers
- Floor extraction and door detection for visually impaired guidance
- Floor Extraction and Door Detection for Visually Impaired Guidance
- A Vision-based Indoor Navigation System for Individuals with Visual Impairment
- Robot vision for the visually impaired
- Optical flow based obstacle avoidance for the visually impaired
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