Papers
1
Total Citations
3
H-Index
1
About
Hasan Kutlu is a researcher whose work lies at the intersection of computer vision and 3D reconstruction, with a particular focus on view planning and quality assessment. His most-cited paper, "Point cloud quality metrics for incremental image-based 3D reconstruction" (2025), addresses a critical challenge in the field: how to optimize the selection of camera poses to maximize the accuracy and completeness of reconstructed 3D models. By developing novel point cloud quality metrics, Kutlu provides a framework for evaluating and improving the output of incremental Structure-from-Motion pipelines. This contribution is essential for applications ranging from cultural heritage preservation to autonomous navigation, where reliable 3D models are paramount. With 3 citations already in a short time, his work is gaining traction among researchers seeking to automate and refine the reconstruction process. Kutlu’s research bridges the gap between theoretical geometry and practical imaging, offering tools that enhance both the efficiency and fidelity of 3D modeling. His focus on view planning—a key bottleneck in the field—positions him as a rising voice in the quest for more intelligent, automated reconstruction systems.
Research Focus
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Top Papers
- 1