Pablo H. Hennings Yeomans

I work in computer vision and pattern recognition applications in biometrics and biomedical imaging. During my PhD in Electrical and Computer Engineering in Carnegie Mellon (2008) I spent most of my time in face recognition and super-resolution. My dissertation is titled "Simultaneous Superresolution and Recognition", a new framework for matching low-resolution probe images to high-resolution images from a gallery, without applying image enhancement. The proposed framework was developed and evaluated for the problem of face recognition. We showed that this approach outperforms the use of super-resolution before face matching, and that it recasts the paradigms of super-resolution design when the purpose is recognition. A summary of this work was recently featured in a MIT Technology Review article: A Face-Finding Search Engine.

Fields of research: pattern recognition, computer vision, machine learning, image and video processing. Specific research areas: image recognition, super-resolution, image enhancement, feature extraction, image segmentation, multiresolution analysis. Application areas: biometric recognition, such as face, palmprint, iris and fingerprint recognition, and biomedical pattern recognition, such as automated clinical diagnosis from biomedical imaging modalities, and proteomics.

My work could not have been possible without the great collaborative spirit of the people I've worked with:
Jelena Kovačević, Simon Baker, B.V.K. Vijaya Kumar, Marios Savvides, Prof. Kovačević's bimagicLab and Prof. Kumar's Pattern Recognition Group.