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Ariel Shamir
Researcher at Interdisciplinary Center Herzliya
Publications - 146
Citations - 11091
Ariel Shamir is an academic researcher from Interdisciplinary Center Herzliya. The author has contributed to research in topics: Object (computer science) & Context (language use). The author has an hindex of 48, co-authored 146 publications receiving 10116 citations. Previous affiliations of Ariel Shamir include University of Texas at Austin & Mitsubishi Electric.
Papers
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Proceedings ArticleDOI
LiveType: a parametric font model based on features and constraints
Ariel Shamir,Ari Rappoport +1 more
Posted Content
Rhythm is a Dancer: Music-Driven Motion Synthesis with Global Structure
Andreas Aristidou,Anastasios Yiannakides,Kfir Aberman,Daniel Cohen-Or,Ariel Shamir,Yiorgos Chrysanthou +5 more
TL;DR: Song et al. as mentioned in this paper presented a music-driven motion synthesis framework that generates long-term sequences of human motions which are synchronized with the input beats, and jointly form a global structure that respects a specific dance genre.
Journal ArticleDOI
Prominent Structures for Video Analysis and Editing
TL;DR: A novel quality measurement of prominent structures in video is measured, a general framework for prominent structure computation is developed, and an efficient hierarchical structure alignment algorithm is developed between a pair of videos.
Patent
Image comparison by asymmetric dynamic warping
Ariel Shamir,Michael Rubinstein +1 more
TL;DR: In this article, the source and target images are segmented, using the image processor, into respective pluralities of sources and targets, respectively including source and targets elements, each array element including a matrix of one or more pixels from a respective image, each of the source arrays having a respective position in the source image, and each of targets corresponding respectively to one of the target arrays based on the respective position.
Patent
System and method for retexturing of images of three-dimensional objects
TL;DR: In this paper, the authors described a system for retexturing portions of surface in a 2D image, where the surface is an image of a 3D object, by analyzing user input and then, in computer memory, generating a 3-D model of the imaged surface.