Karen Panetta
Papers
8
Total Citations
65
H-Index
4
About
Karen Panetta is a leading researcher in the intersection of computer vision, robotics, and human visual system (HVS) algorithms. Her work focuses on enhancing robotic perception and autonomous systems by mimicking the biological processing of the human eye. A key contribution is the development of novel image enhancement techniques, including a color contrast enhancement algorithm based on the alpha weighted quadratic filter, which improves visual data for robotic applications. She has also pioneered low-cost facial recognition systems for unmanned aerial vehicles (UAVs) and autonomous platforms, enabling real-time detection and recognition in real-world environments. Her work on the TDMEC metric provides a new standard for evaluating color image quality in vision systems, addressing noise from poor illumination and sensor electronics. With over 20 citations for her foundational work on color contrast enhancement, Panetta’s research has significant impact on search and rescue, border surveillance, and autonomous navigation. She has also explored multisensory foresight for embodied agents, predicting future sensory states to improve learning in robots and drones. Her innovative use of eye-tracking for hands-free aerial surveillance further demonstrates her commitment to practical, human-centered robotics solutions.
Research Focus
Key Achievements
Top Papers
- 1A new color contrast enhancement algorithm for robotic applications20 citations · 2012
- 2
- 3
- 4Human visual system inspired object detection and recognition8 citations · 2012
- 5A Framework for Multisensory Foresight for Embodied Agents4 citations · 2021
- 6
- 7Autonomous facial recognition based on the human visual system3 citations · 2015
- 8Robust template based corner detection algorithms for robotic vision2 citations · 2015