Thangarajah Akilan

Lakehead University, University of Windsor

Papers

Total Citations

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About

Thangarajah Akilan is a computer vision researcher whose work spans autonomous navigation, augmented reality, and video analysis. His key research areas include Simultaneous Localization And Mapping (SLAM) for self-driving cars, vision-based registration for augmented reality, and video foreground localization. Akilan’s major contributions lie in advancing multimodal fusion techniques—specifically, his work on weight and score fusion for SLAM (2020, 7 citations) enhances trajectory prediction in autonomous navigation robots by integrating multiple sensor modalities. He also conducted a comprehensive survey on vision-based registration for augmented reality (2015, 7 citations), systematically cataloging techniques that overlay virtual objects onto real-world scenes. In video analysis, Akilan explored the evolution of foreground localization from traditional methods to deep learning (2018, 4 citations), addressing detection of visual attention regions critical for applications like video surveillance and human-machine interaction. His research demonstrates a clear trajectory from foundational surveys to applied fusion methods, with each paper contributing to practical improvements in autonomous systems and AR technologies. Akilan’s work is particularly valuable for researchers seeking to understand the progression from classical computer vision approaches to modern deep learning solutions in real-time perception tasks.