Stefan Lanser
Papers
1
Total Citations
17
H-Index
1
About
Stefan Lanser is a computer vision researcher whose work centers on the recognition and modeling of articulated 3D objects from monocular imagery. His most cited contribution, "Hierarchical recognition of articulated objects from single perspective views" (2002, 17 citations), introduces a pioneering framework that represents objects as compositions of rigid components linked by explicit kinematic constraints, such as rotational and translational joints. This hierarchical approach enables robust object detection and pose estimation from a single viewpoint, addressing a fundamental challenge in understanding complex, moving structures in video. Lanser's work has been influential in advancing model-based vision, particularly for applications in robotics and human-computer interaction, where interpreting articulated motion is critical. While his citation count reflects a focused but impactful contribution, his research stands out for its elegant integration of geometric modeling and recognition, laying groundwork for later developments in articulated object tracking and 3D scene understanding.
Research Focus
Key Achievements
Top Papers
- 1