Description
This work delves into the intricate relationship between Riemannian geometry and computer vision, showcasing how these mathematical concepts can enhance computational methodologies in visual analysis. The authors, Pavan K Turaga and Anuj Srivastava, provide a thorough examination of Riemannian geometric computations, unveiling their potential applications within various computer vision tasks.
Through a blend of theoretical foundations and practical examples, the book illustrates how Riemannian frameworks can be leveraged to improve object recognition, image processing, and pattern analysis. Readers are invited to explore advanced techniques that bridge mathematics and technology, ultimately paving the way for innovative approaches in the field of computer vision.
Through a blend of theoretical foundations and practical examples, the book illustrates how Riemannian frameworks can be leveraged to improve object recognition, image processing, and pattern analysis. Readers are invited to explore advanced techniques that bridge mathematics and technology, ultimately paving the way for innovative approaches in the field of computer vision.
Détails du livre
Format
Relié
Pages
397 pages
Langue
Anglais
Publié
nov. 18, 2015
Éditeur
Springer
ISBN-10
3319229567
ISBN-13
9783319229560