Matteo Munaro

University of Padua

Papers

20

Total Citations

732

H-Index

13

About

Matteo Munaro is a computer vision and robotics researcher whose work centers on human perception, people tracking, and RGB-D sensor-based systems for intelligent environments and service robots. His most significant contributions lie in developing fast, robust algorithms for detecting and tracking people in real-world scenarios, including the challenging problem of identifying individuals within crowds or groups. Munaro's most cited work, "Fast RGB-D People Tracking for Service Robots" (2014, 163 citations), alongside "Tracking People within Groups with RGB-D Data" (2012, 142 citations), established him as a key figure in mobile robot perception, introducing novel depth-based sub-clustering methods that dramatically improved tracking reliability on moving platforms. His development of **OpenPTrack** — an open-source multi-camera calibration and people tracking framework — reflects a commitment to accessible, scalable solutions for camera network deployments, garnering nearly 100 citations. Beyond tracking, Munaro has advanced people re-identification using skeletal keypoints and face recognition, and explored human action recognition through 3D optical flow from colored point clouds. His work spans both service robotics and industrial safety environments, demonstrating broad real-world applicability. Collectively, his research has accumulated over 600 citations, underscoring his meaningful influence on human-aware robotics and intelligent surveillance systems.

Research Focus

Key Achievements

13
H-Index
20
Papers
732
Total Citations
37
Avg Citations/Paper
🏆 Most Cited Paper
Fast RGB-D people tracking for service robots
163 citations · 2014
📈 Most Prolific Year: 2014 (4 Papers)
🤝 Key Collaborators: 22
🏛 Institutions: University of Padua

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago