Okko Lohmann

Papers

Total Citations

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About

Okko Lohmann is a researcher whose work lies at the intersection of cognitive robotics and computer vision, with a particular focus on human-robot interaction. His most-cited paper, "Directed attention - a cognitive vision system for a mobile robot" (2009, 6 citations), introduces a pioneering method that integrates bottom-up saliency, texture descriptors, and top-down attention mechanisms. This approach allows a mobile robot to dynamically direct its focus toward arbitrary objects during interaction, moving beyond simple feature extraction to enable more natural, context-aware visual behavior. Lohmann’s contribution is significant for advancing how robots perceive and prioritize visual information, bridging low-level sensory processing with higher cognitive goals. While his citation count reflects a focused, early-career impact, his work on directed attention systems has laid groundwork for more adaptive robotic perception. His research is particularly valuable for students and researchers exploring attention-based vision systems, offering a clear example of how combining computational models of human attention can improve robotic autonomy and interaction quality.