Papers
66
Total Citations
1,103
H-Index
18
About
Miguel Cazorla is a prominent computer scientist whose research spans robotics, computer vision, and assistive technology, with particular expertise in socially assistive robots and 3D scene understanding. Based at the University of Alicante, Cazorla has made significant contributions to the development of robotic systems designed to support vulnerable populations, including older adults and people with disabilities. His landmark PHAROS project — a Physical Assistant Robot System that recommends and monitors exercise for the elderly — has drawn considerable attention, accumulating over 70 citations and spawning an improved successor, demonstrating sustained innovation in the field. His work on socially assistive robots for older adults and autism has garnered nearly 80 citations, underscoring the real-world relevance of his research agenda. Cazorla has also advanced foundational techniques in 3D point cloud processing, contributing influential methods for geometric compression, noise filtering, and downsampling that have each attracted over 45 citations. His involvement in the prestigious ImageCLEF benchmarking challenges — contributing overview papers cited over 100 and 49 times respectively — reflects his stature within the broader computer vision community. Rounding out his portfolio, his work on monocular RGB camera-based hand pose estimation for robot teleoperation highlights his commitment to practical, human-centered robotics solutions.
Research Focus
Key Achievements
Top Papers
- 1ImageCLEF 2014: Overview and Analysis of the Results101 citations · 2014
- 2
- 3Geometric 3D point cloud compression72 citations · 2014
- 4PHAROS—PHysical Assistant RObot System72 citations · 2018
- 5ImageCLEF 2013: The Vision, the Data and the Open Challenges49 citations · 2013
- 6Point cloud data filtering and downsampling using growing neural gas45 citations · 2013
- 7
- 8PHAROS 2.0—A PHysical Assistant RObot System Improved35 citations · 2019
- 9A Socially Assistive Robot for Elderly Exercise Promotion35 citations · 2019
- 10A Comparative Study of Registration Methods for RGB-D Video of Static Scenes32 citations · 2014