Papers
1
Total Citations
3
H-Index
1
About
Yue Su is a researcher specializing in computer vision and autonomous robotics, with a particular focus on depth perception and stereo vision systems. Their most notable work addresses a fundamental challenge in binocular stereo vision: the problem of depth holes that arise when matching algorithms fail to correlate corresponding points across image pairs. In their 2023 paper, "Depth Hole Filling and Optimizing Method Based on Binocular Parallax Image," Su proposes innovative techniques to reconstruct missing depth information in disparity maps, directly enhancing the reliability of environment perception for autonomous robots operating in dynamic, real-world conditions. This contribution is especially significant given the growing demand for robust autonomous systems in industrial, medical, and consumer robotics applications. By improving the completeness and accuracy of depth maps derived from binocular stereo vision, Su's work helps bridge a critical gap between theoretical algorithms and practical deployment. Though still early in their citation trajectory with 3 citations, the research addresses a technically meaningful problem that positions Su as an emerging contributor to the robotics perception and computer vision communities.
Research Focus
Key Achievements
Top Papers
- 1