Company Filing History:
6 out of 27 
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Years Active: 2011-2013
Title: Mircea Ionita: Innovator in Statistical Face Modelling
Introduction
Mircea Ionita is a notable inventor based in Galway, Ireland. He has made significant contributions to the field of statistical face modelling, with a focus on techniques that enhance the understanding of facial characteristics in digital images. With a total of 6 patents to his name, Ionita's work is recognized for its innovative approach and practical applications.
Latest Patents
One of Ionita's latest patents is titled "Separating directional lighting variability in statistical face modelling based on texture space decomposition." This technique involves determining characteristics of a face or other objects within a scene captured in a digital image. The process includes acquiring an image and applying a linear texture model constructed from a training data set. This model comprises a class of objects, including a first subset of model components that depend on directional lighting variations and a second subset that remains independent of such variations. The model is fitted to the face or object by adjusting individual values of the model components. Ultimately, this fit allows for the determination of specific characteristics of the face or object in the scene.
Career Highlights
Throughout his career, Mircea Ionita has worked with esteemed organizations such as the National University of Ireland and Adeia Semiconductor Bonding Technologies Inc. His experience in these institutions has contributed to his expertise in the field of statistical modelling and image processing.
Collaborations
Ionita has collaborated with notable colleagues, including Peter Corcoran and Ioana Bacivarov. These partnerships have further enriched his research and development efforts in the realm of face modelling technologies.
Conclusion
Mircea Ionita stands out as an influential inventor in the field of statistical face modelling. His innovative patents and collaborations reflect his commitment to advancing technology in understanding facial characteristics through digital imaging.