Sara Casao
Papers
3
Total Citations
17
H-Index
2
About
Sara Casao is a researcher at the forefront of intelligent robotic perception, with her work centered on distributed multi-target tracking, active perception, and person re-identification. Her most impactful contribution, "Distributed multi-target tracking and active perception with mobile camera networks" (2023, 11 citations), addresses the critical challenge of enabling networks of mobile cameras to collaboratively track multiple targets while actively planning their own viewpoints—a key capability for autonomous surveillance and human-robot interaction. Casao also advances open-world person re-identification with a self-adaptive gallery construction method (2023, 4 citations), allowing robotic systems to dynamically update their knowledge of individuals over time, essential for long-term tracking and navigate-and-seek tasks. To support rigorous evaluation, she developed a framework for fast prototyping of photo-realistic environments with multiple pedestrians (2023, 2 citations), enabling researchers to generate accurate synthetic data for testing perception systems. Her work bridges the gap between simulation and real-world deployment, providing both theoretical foundations and practical tools for robots that must perceive, track, and interact with people in complex, dynamic environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3