Papers
13
Total Citations
392
H-Index
8
About
Marco Leo is a leading researcher at the intersection of computer vision, assistive robotics, and affective computing, with a primary focus on automatic emotion recognition and its application in therapeutic interventions for Autism Spectrum Disorder (ASD). His work has fundamentally advanced how machines perceive and respond to human emotional cues, particularly through the use of Histograms of Oriented Gradients (HOG) for facial expression recognition—a comprehensive study on this topic has garnered 183 citations. Leo’s major contributions lie in developing robot-assisted systems that stimulate social interaction in children with ASD, as demonstrated in his highly cited 2015 work on automatic emotion recognition in robot-child interaction (69 citations) and his 2017 study on social interaction mechanisms using humanoid robots (39 citations). He has also explored low-cost, calibration-free gaze estimation for soft biometrics and real-time gender-based behavior systems for human-robot interaction. Notably, his 2021 pre-study comparing robot-based versus computer-based training for emotional expression in children with ASD (37 citations) highlights his ongoing commitment to translating computer vision research into tangible assistive technologies. With over 380 total citations across his most impactful works, Leo’s research continues to shape the fields of socially assistive robotics and computer vision for healthcare.
Research Focus
Key Achievements
Top Papers
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- 6Active Surveillance of Dynamic Environments using a Multi-Agent System9 citations · 2010
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- 8Real-Time Gender Based Behavior System for Human-Robot Interaction9 citations · 2014
- 9Special issue on Assistive Computer Vision and Robotics - Part I7 citations · 2016
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