Papers
1
Total Citations
19
H-Index
1
About
Chenle Ye is a researcher whose work sits at the intersection of assistive technology, computer vision, and 3D data processing. Their most recognized contribution is the development of **NCC-RANSAC**, a fast and robust plane extraction method introduced in a 2013 paper that has garnered 19 citations. This technique was specifically designed to improve navigation for a **smart cane for the visually impaired**, addressing a critical limitation of generic RANSAC plane extraction, which can over-extract planes or fail in multi-step scenes by producing slant planes that straddle distinct surfaces. By refining how 3D range data is interpreted, Ye’s work directly enhances the reliability of real-time environmental mapping for assistive devices. Though their citation count is modest, the practical impact is significant—enabling safer, more accurate pathfinding for users with visual impairments. Ye’s research exemplifies how targeted algorithmic innovations can solve real-world problems, bridging the gap between theoretical computer vision and life-changing applications in accessibility and mobility.
Research Focus
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Top Papers
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