Christophe Montagne

Centre National de la Recherche Scientifique, Université d'Évry Val-d'Essonne

Papers

Total Citations

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About

Christophe Montagne’s research lies at the intersection of mobile robotics, computer vision, and human-robot interaction, with a particular focus on enabling robots to perceive and navigate indoor environments. His most cited work, “Global Interior Robot Localisation by a Colour Content Image Retrieval System” (2007, 9 citations), introduces a novel global localisation method that uses colour-based image retrieval to determine a robot’s coarse position in structured indoor spaces. This approach leverages an original colour quantisation technique based on the baker’s transformation, demonstrating Montagne’s innovative use of colour theory for practical robotics. In later work, “A Depth-based Approach for 3D Dynamic Gesture Recognition” (2015, 4 citations), he extends his expertise to human-robot interaction, using Kinect depth data and skeleton tracking to compute upper-body angles for recognising 3D dynamic gestures. Earlier, in “How to Choose the Best Color Space for the Guidance of an Indoor Robot?” (2002, 2 citations), Montagne explored optimal colour spaces for robot guidance, motivated by assistive technologies for disabled individuals. Though his citation counts are modest, Montagne’s contributions are foundational in colour-based localisation and gesture recognition for service robotics, reflecting a career dedicated to making robots more intuitive and capable in human-centred environments.