Marcela Mera-Trujillo
Papers
1
Total Citations
7
H-Index
1
About
Dr. Marcela Mera-Trujillo is a computer vision researcher whose work centers on advancing keypoint detection and matching—a foundational task underpinning applications from 3D reconstruction and structure from motion to augmented reality and robotics. Her most cited work, "Self-supervised Interest Point Detection and Description for Fisheye and Perspective Images" (2023, 7 citations), tackles a critical challenge: adapting deep learning-based feature extraction to wide-angle fisheye imagery, which suffers from severe distortion that traditional methods like SIFT handle poorly. By proposing a self-supervised framework that learns robust, viewpoint-invariant features across both perspective and fisheye domains, Dr. Mera-Trujillo’s contribution enables more reliable visual correspondence in real-world settings—such as autonomous navigation and immersive AR/VR—where non-standard cameras are common. Her approach reduces reliance on costly manual annotations while improving performance on distorted inputs, marking a practical step forward for field-deployable vision systems. Though early in her career, her work has already garnered attention for bridging a gap between classical feature engineering and modern deep learning, positioning her as an emerging voice in robust visual perception for challenging imaging conditions.
Research Focus
Key Achievements
Top Papers
- 1