Kenichi Kanatani Knihy

Focusing on geometric interpretations, this book bridges linear algebra with pattern information processing, particularly in analyzing high-dimensional data relevant to computer vision and graphics. It covers essential concepts like projection, spectral decomposition, and singular value decomposition, illustrating their applications in least-squares solutions and covariance matrices. The text emphasizes visualizing abstract spaces and includes practical examples, such as reconstructing 3D locations from camera views, to enhance understanding of linear algebra's role in data analysis amidst noise.

The book delves into the computational analysis of 3D rotation, emphasizing its crucial role in various applications such as 3D sensing with cameras and sensors, modeling for computer vision and graphics, and robot motion control and simulation. By prioritizing computational techniques over traditional motion analysis, it offers a focused exploration of how 3D rotation impacts these fields, making it a valuable resource for professionals and researchers interested in advanced 3D applications.