Papers
2
Total Citations
8
H-Index
2
About
Serge Miguet’s research focuses on computer vision and intelligent video surveillance, with key contributions in real-time multi-object tracking and scene understanding. His most cited work, “Real-Time Multi-object Tracking with Occlusion and Stationary Objects Handling for Conveying Systems” (2016, 5 citations), addresses critical challenges in industrial environments by developing robust algorithms that manage occlusions and stationary objects—enabling reliable tracking on conveyor belts and similar settings. This work has practical implications for automation and logistics. In another notable study, “Skyline-based approach for natural scene identification” (2016, 3 citations), Miguet pioneers the use of the skyline—the boundary between sky and ground—as a geometric cue for geo-localization and aerial robotics. By leveraging this natural feature, his method enhances scene recognition in unstructured outdoor environments, offering a novel alternative to traditional landmark-based approaches. Though his citation counts are modest, Miguet’s contributions demonstrate focused innovation in applied computer vision, particularly for real-world systems where reliability under occlusion and environmental variability is paramount. His work bridges theoretical vision techniques with practical deployment in conveying systems and autonomous navigation.
Research Focus
Key Achievements
Top Papers
- 1
- 2Skyline-based approach for natural scene identification3 citations · 2016