Daniel Fischer
Papers
1
Total Citations
9
H-Index
1
About
Daniel Fischer is a researcher in computer vision and 3D object recognition, with a focus on interpreting sparse, segmented range data. His most cited work, "Intrinsic line features and contour metric for locating 3-D objects in sparse, segmented range images" (1999), introduced a novel approach for robustly identifying objects from limited geometric cues. By developing intrinsic line features and a contour metric, Fischer enabled more reliable matching in cluttered or incomplete scenes—a critical challenge for autonomous systems and robotics. Though his citation count is modest, this foundational paper has influenced subsequent work in 3D perception and object localization. Fischer's contributions lie in advancing practical methods for spatial reasoning, bridging the gap between raw sensor data and meaningful object recognition. His research underscores the importance of feature extraction in low-resolution environments, offering tools that remain relevant for modern applications in automation and augmented reality.
Research Focus
Key Achievements
Top Papers
- 1