E
Eyal Ofek
Researcher at Microsoft
Publications - 281
Citations - 11705
Eyal Ofek is an academic researcher from Microsoft. The author has contributed to research in topics: Virtual reality & Haptic technology. The author has an hindex of 46, co-authored 270 publications receiving 9984 citations. Previous affiliations of Eyal Ofek include Hebrew University of Jerusalem.
Papers
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Proceedings ArticleDOI
Detecting text in natural scenes with stroke width transform
TL;DR: A novel image operator is presented that seeks to find the value of stroke width for each image pixel, and its use on the task of text detection in natural images is demonstrated.
Journal ArticleDOI
Full-frame video stabilization with motion inpainting
TL;DR: This work proposes a practical and robust approach of video stabilization that produces full-frame stabilized videos with good visual quality and develops a complete video stabilizer which can naturally keep the original image quality in the stabilized videos.
Proceedings ArticleDOI
Haptic Retargeting: Dynamic Repurposing of Passive Haptics for Enhanced Virtual Reality Experiences
TL;DR: The study results indicate that all the haptic retargeting techniques improve the sense of presence when compared to typical wand-based 3D control of virtual objects, and a hybrid technique which combines both world and body manipulation achieves the highest satisfaction and presence scores.
Proceedings ArticleDOI
RoomAlive: magical experiences enabled by scalable, adaptive projector-camera units
Brett R. Jones,Rajinder Sodhi,Michael Murdock,Ravish Mehra,Hrvoje Benko,Andrew D. Wilson,Eyal Ofek,Blair MacIntyre,Nikunj Raghuvanshi,Lior Shapira +9 more
TL;DR: This work investigates the design space of gaming experiences that are possible with RoomAlive, explores methods for dynamically mapping content based on room layout and user position, and showcases four experience prototypes that demonstrate the novel interactive experiences possible with the system.
Patent
Mode information displayed in a mapping application
TL;DR: In this article, an object of interest can be identified by monitoring a user activity or inactivity with regard to a displayed map, if the user hovers a pointing device over an object within the displayed map for longer than a predetermined amount of time.