Lei Han

Papers

Total Citations

H-Index

About

Lei Han is a researcher whose work sits at the intersection of computer vision and image processing, with a particular focus on geometric scene understanding. His most recognized contribution to date is his 2016 paper on vanishing point detection and line classification using Binary Particle Swarm Optimization (BPSO), which has garnered 6 citations within the field. This work addresses a fundamental challenge in computer vision — accurately identifying vanishing points in images, which is critical for applications ranging from autonomous driving and robot navigation to architectural reconstruction and augmented reality. By leveraging the optimization capabilities of BPSO, Han's approach offers an intelligent and efficient framework for classifying line segments and estimating scene geometry, contributing a meaningful methodological advance to the field. While Han's publication record as represented here is still emerging, the technical depth of this contribution signals a researcher with strong foundations in optimization-driven approaches to visual perception. Students and researchers working on scene understanding, perspective geometry, or swarm intelligence-based computer vision methods would find Han's work a relevant and thought-provoking reference point in their own explorations.