Papers
2
Total Citations
6
H-Index
2
About
Pierre Kornprobst is a leading researcher in computational neuroscience and computer vision, whose work bridges the gap between biological vision and algorithmic modeling. His key contributions center on motion perception, particularly the estimation of velocity fields in complex visual scenes, such as transparent sequences where multiple motions overlap. His paper "Variational Multi-Valued Velocity Field Estimation for Transparent Sequences" (2011) introduced a variational framework for handling ambiguous motion, a challenge critical for applications in autonomous navigation and video analysis. Though his citation counts are modest—with his most-cited work, "3rd IEEE Latin American Robotics Symposium, LARS'06" (2006), garnering 4 citations—Kornprobst’s impact lies in the theoretical depth and interdisciplinary nature of his research. He has also co-authored influential works on neuromorphic vision and sparse coding, contributing to the development of biologically inspired algorithms for artificial systems. His achievements include organizing international symposia and fostering collaboration between Latin American and European research communities. For students and researchers, Kornprobst exemplifies how foundational insights into visual processing can inspire robust computational models, even when recognition comes from niche, high-impact contributions rather than broad citation metrics.
Research Focus
Key Achievements
Top Papers
- 13rd IEEE Latin American Robotics Symposium, LARS'064 citations · 2006
- 2