Sean Ryan Francesco Fanello

Title: Sean Ryan Francesco Fanello: Innovator in Visual Content Technology

Introduction

Sean Ryan Francesco Fanello is a prominent inventor based in Bellevue, WA (US). He has made significant contributions to the field of visual content technology, holding a total of 5 patents. His work focuses on advanced techniques for depth determination and correspondence estimation in visual content items.

Latest Patents

One of his latest patents is titled "Determining depth from structured light using trained classifiers." This invention involves techniques for determining depth for a visual content item using machine-learning classifiers. It includes obtaining a visual content item of a reference light pattern projected onto an object and determining shifts in locations of pixels relative to other pixels representing the reference light pattern. Disparity, and thus depth, for pixels may be determined by executing one or more classifiers trained to identify disparity based on these shifts.

Another notable patent is "Computerized correspondence estimation using distinctively matched patches." This patent describes methods for determining correspondences in content items using a trained decision tree to detect distinctive matches between portions of content items. The techniques involve processing patches associated with different content items and determining that they correspond based on their association with the same leaf node of the decision tree.

Career Highlights

Sean Ryan Francesco Fanello is currently employed at Microsoft Technology Licensing, LLC, where he continues to innovate in the field of visual technology. His work has been instrumental in advancing the capabilities of machine learning in visual content analysis.

Collaborations

He has collaborated with notable colleagues such as Shahram Izadi and Cem Keskin, contributing to a dynamic and innovative work environment.

Conclusion

Sean Ryan Francesco Fanello is a key figure in the realm of visual content technology, with a focus on machine learning applications. His patents reflect a commitment to advancing the field and enhancing the capabilities of visual analysis.