Tomáš Ižo
Tomáš Ižo is an engineering director in the Machine Perception group at Google Research. He leads a team of engineers and scientists pursuing applied research in the areas of video understanding, video summarization, computational imaging, photography and videography, mobile perceptual computing, creative tools, and scalable, cross-platform media processing infrastructure. The team's work contributes to a wide range of products across Google and Alphabet, such as video understanding for YouTube, enabling content-based video search in Photos, imaging and video features in the Pixel camera, Cloud Platform APIs, video previews in Google Search, improving the quality of ads, and many more.
Recent work from the team includes improving YouTube thumbnails with deep neural nets, the YouTube-8M dataset for video understanding research, Motion Stills apps on Android and iOS for machine intelligence-enabled microvideo creation, and learned image super-resolution (RAISR).
Tomáš came to Google by way of the Massachusetts Institute of Technology, where he received a Ph.D. in computer science in 2007. His doctoral research focused on motion tracking, scene activity analysis and visual attention models. Prior to attending MIT, Tomas received a B.S. in computer science from Yale University, where he did undergraduate research in computational models of visual cortical processing.
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Unsupervised Modeling of Object Tracks for Fast Anomaly Detection
Moving object segmentation using super-resolution background models
Joshua Migdal
Chris Stauffer
Workshop on Omnidirectional Vision, Camera Networks and Non-Classical Cameras (2005)
Simultaneous pose recovery and camera registration from multiple views of a walking person
Simultaneous Pose Estimation and Camera Calibration from Multiple Views
Cortical connections and early visual function: Intra- and inter-columnar processing
