Computer Vision Metrics: Survey, Taxonomy, and Analysis
by Scott Krig
Publisher: Springer 2014
Number of pages: 498
Provides an extensive survey and analysis of over 100 current and historical feature description and machine vision methods, with a detailed taxonomy for local, regional and global features. This book provides necessary background to develop intuition about why interest point detectors and feature descriptors actually work, how they are designed, with observations about tuning the methods for achieving robustness and invariance targets for specific applications.
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by Cesare Rossi - InTech
The book provides new ideas, original results and practical experiences regarding service robotics. It is only a small example of this research activity, but it covers a great deal of what has been done in the field recently.
by Dilip K. Prasad - arXiv
We propose a new object detection/recognition method, which improves over the existing methods in every stage of the object detection/recognition process. In addition to the usual features, we propose to use geometric shapes as additional features.
by David Marshall - Cardiff School of Computer Science
From the table of contents: Image Acquisition: 2D Image Input, 3D imaging; Image processing: Fourier Methods, Smoothing Noise; Edge Detection; Edge Linking; Segmentation; Line Labelling; Relaxation Labelling; Optical Flow; Object Recognition.
by Asim Bhatti (ed.) - InTech
The topics covered in this book include fundamental theoretical aspects of robust stereo correspondence estimation, novel and robust algorithms, hardware implementation for fast execution, neuromorphic engineering, probabilistic analysis, etc.