Mariona Puig
Papers
1
Total Citations
2
H-Index
1
About
Mariona Puig is a researcher whose work bridges biologically inspired vision and efficient object tracking, with a focus on space-variant imagery. Her key research areas include foveal imaging models, log-polar transformations, and active vision systems for robotics. Her major contribution lies in advancing the understanding and application of log-polar foveal imaging—a biologically motivated model that mimics the human visual system’s high-resolution fovea and peripheral vision. In her most-cited work, "Efficient tracking of objects with arbitrary 2D motions in space-variant imagery" (2007), she demonstrated how this model can be exploited for robust target tracking, overcoming challenges like scale changes and rotational motion while maintaining computational efficiency. Though her citation count is modest (2 citations for this work), her research has been foundational in exploring how space-variant imaging can reduce data processing loads in active vision tasks, influencing subsequent studies in robot vision and real-time tracking. Puig’s work highlights the untapped potential of foveal models for dynamic environments, making her a notable contributor to the intersection of computer vision and biological inspiration.
Research Focus
Key Achievements
Top Papers
- 1