- Mastering OpenCV 4
- Roy Shilkrot David Millán Escrivá
- 310字
- 2021-07-02 14:47:32
About the authors
Roy Shilkrot is an assistant professor of computer science at Stony Brook University, where he leads the Human Interaction group. Dr. Shilkrot's research is in computer vision, human-computer interfaces, and the cross-over between these two domains, funded by US federal, New York State, and industry grants. Dr. Shilkrot graduated from the Massachusetts Institute of Technology (MIT) with a PhD, and has authored more than 25 peer-reviewed papers published at premier computer science conferences, such as CHI and SIGGRAPH, as well as in leading academic journals such as ACM Transaction on Graphics (TOG) and ACM Transactions on Computer-Human Interaction (ToCHI). Dr. Shilkrot is also a co-inventor of several patented technologies, a co-author of a number of books, serves on the scientific advisory board of numerous start-up companies, and has over 10 years of experience as an engineer and an entrepreneur.
David Millán Escrivá was eight years old when he wrote his first program on an 8086 PC in Basic, which enabled the 2D plotting of basic equations. In 2005, he finished his studies in IT through the Universitat Politécnica de Valenci with honors in human-computer interaction supported by computer vision with OpenCV (v0.96). He had a final project based on this subject and published it on HCI Spanish congress. He has worked with Blender, an open source, 3D software project, and worked on his first commercial movie, Plumiferos - Aventuras voladoras, as a computer graphics software developer. David now has more than 10 years of experience in IT, with experience in computer vision, computer graphics, and pattern recognition, working with different projects and start-ups, applying his knowledge of computer vision, optical character recognition, and augmented reality. He is the author of the DamilesBlog blog, where he publishes research articles and tutorials about OpenCV, computer vision in general, and optical character recognition algorithms.
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