Papers
1
Total Citations
4
H-Index
1
About
Marouane Boui is a computer vision researcher whose work focuses on advancing human detection and scene understanding through unconventional imaging modalities. His primary research areas include omnidirectional vision, spherical image analysis, and human-robot interaction. Boui’s most notable contribution is his pioneering approach to human detection in spherical images, a challenging domain where traditional perspective-based methods fail due to the geometric distortions of 360-degree cameras. In his 2016 paper, “New approach for human detection in spherical images,” he introduced a novel framework that adapts detection algorithms to the equirectangular projection, enabling robust identification of humans across the full panoramic field of view. This work has garnered 4 citations, laying foundational groundwork for applications in robotics, surveillance, and autonomous navigation where wide-angle sensing is critical. Boui’s research addresses a key gap in computer vision—leveraging the unique advantages of omnidirectional cameras, such as single-sensor 360-degree coverage, while overcoming the algorithmic challenges they present. His contributions are particularly valuable for students and researchers exploring non-conventional camera systems, offering practical insights into adapting standard detection pipelines for spherical imagery. Boui’s work continues to influence the development of more versatile and efficient human-aware systems in dynamic environments.
Research Focus
Key Achievements
Top Papers
- 1New approach for human detection in spherical images4 citations · 2016