Non-rigid Image Registration Using Geometric Features and Local Salient Region Features

Jinzhong Yang; Rick S. Blum; James P. Williams; Yiyong Sun; Chenyang Xu

doi:10.1109/CVPR.2006.208

2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06)

Non-rigid Image Registration Using Geometric Features and Local Salient Region Features

Year: 2006, Volume: 1, Pages: 825-832

DOI Bookmark: 10.1109/CVPR.2006.208

Authors

Jinzhong Yang, Lehigh University, Bethlehem, PA 18015, USA
Rick S. Blum, Lehigh University, Bethlehem, PA 18015, USA
James P. Williams, Siemens Corporate Research, Princeton, NJ
Yiyong Sun, Siemens Corporate Research, Princeton, NJ
Chenyang Xu, Siemens Corporate Research, Princeton, NJ

Abstract

Written texts have perhaps never been so widely used as they are in today's social media context, with people constantly writing, sharing, commenting, getting involved. At the same time, Linked Data is emerging as an increasingly important topic, and research in this area has resulted in massive amounts of structured linguistic data. In this climate, we intend to analyze how linked data can help to structure and extract meaning from social media's short, informal and context dependent texts, with an emphasis on real-life applications.

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Non-rigid Image Registration Using Geometric Features and Local Salient Region Features

Authors

Abstract

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