Amna Shabbir
Papers
1
Total Citations
2
H-Index
1
About
Amna Shabbir is a researcher focused on advancing 3D geospatial data acquisition and processing, with particular expertise in point cloud classification and low-cost surveying systems. Her work centers on developing accessible methodologies for extracting meaningful information from complex 3D datasets, bridging the gap between expensive commercial solutions and practical, real-world applications. Her most cited paper, "Parametric Classification of Furniture From Point Cloud Developed Using Low Cost Trolley Based Laser Scanning System" (2023, 2 citations), introduces a novel parametric classification approach that identifies indoor and outdoor furniture objects within 3D Cartesian point clouds. A key achievement of this work is the development of a custom, low-cost trolley-based scanning system using orthogonal sensors, demonstrating her commitment to democratizing 3D surveying technology. This innovation makes detailed environmental modeling more accessible for applications in architecture, urban planning, and facility management. Shabbir’s contributions highlight the potential of affordable, parametric methods to transform how we interpret and interact with spatial data, offering a practical pathway for researchers and practitioners working with limited resources.
Research Focus
Key Achievements
Top Papers
- 1