Oytun Akman

Papers

Total Citations

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About

Oytun Akman's research lies at the intersection of computer vision and robotics, with a focus on robust augmented reality and autonomous object manipulation. His work addresses fundamental challenges in enabling machines to perceive and interact with their environments through visual data. Akman’s major contributions include developing methods for exploiting 3D information to direct visual attention and improve object recognition, particularly in cluttered or dynamic settings. His 2012 paper on "Robust Augmented Reality" (4 citations) explores how computer vision systems can replace human perception in tasks requiring real-time environmental interfacing, while his 2009 work on "Exploitation of 3D Information for Directing Visual Attention and Object Recognition" (3 citations) advances efficient object detection for robot actuation. Additionally, his 2011 study on "Object Recognition and Localisation for Item Picking" (3 citations) addresses the practical challenge of enabling robots to locate and grasp items in high-resolution imaging environments. Though his citation counts are modest, Akman’s research contributes to the foundational technologies behind autonomous systems, offering insights into how computational power and 3D data can enhance machine vision for real-world applications. His work remains relevant for students and researchers exploring vision-based robotics and augmented reality.