Tammam Tillo

Papers

Total Citations

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About

Tammam Tillo is a researcher whose work lies at the intersection of computer vision, image processing, and 3D scene understanding. His key contributions focus on leveraging depth information to enhance visual analysis, with a particular emphasis on planar surface detection—a critical component for applications ranging from robotic navigation to 3D reconstruction. In his notable 2014 work, "Depth-map driven planar surfaces detection," Tillo introduced a method that exploits the inherent structure of man-made environments, where planar surfaces are ubiquitous. By using depth maps as a geometric cue, his approach improves the accuracy of segmenting and reconstructing scenes, offering a robust foundation for autonomous systems. Though his most cited paper has garnered 10 citations, the impact of his research extends into practical domains, demonstrating how depth-driven techniques can simplify complex visual tasks. Tillo’s work is especially valuable for students and researchers exploring efficient, geometry-aware algorithms in computer vision, as it bridges the gap between raw sensor data and meaningful scene interpretation.