Representations and Techniques for 3D Object Recognition and Scene Interpretation by Derek Hoiem English | PDF(True) | 2011 | 171 Pages | ISBN : 1608457281 | 29.91 MB
One of the grand challenges of artificial intelligence is to enable computers to interpret 3D scenes and objects from imagery. This book organizes and introduces major concepts in 3D scene and object representation and inference from still images, with a focus on recent efforts to fuse models of geometry and perspective with statistical machine learning.
Composing Fisher Kernels from Deep Neural Models: A Practitioner's Approach by Tayyaba Azim English | PDF,EPUB | 2018 | 69 Pages | ISBN : 331998523X | 4.22 MB
This book shows machine learning enthusiasts and practitioners how to get the best of both worlds by deriving Fisher kernels from deep learning models. In addition, the book shares insight on how to store and retrieve large-dimensional Fisher vectors using feature selection and compression techniques. Feature selection and feature compression are two of the most popular off-the-shelf methods for reducing data’s high-dimensional memory footprint and thus making it suitable for large-scale visual retrieval and classification.
Deformation Models: Tracking, Animation and Applications by Manuel González Hidalgo English | PDF | 2013 | 301 Pages | ISBN : 9400754450 | 10.2 MB
The computational modelling of deformations has been actively studied for the last thirty years. This is mainly due to its large range of applications that include computer animation, medical imaging, shape estimation, face deformation as well as other parts of the human body, and object tracking. In addition, these advances have been supported by the evolution of computer processing capabilities, enabling realism in a more sophisticated way.