2D Object Detection and Recognition. Models, Algorithms, and Networks.pdf

2D Object Detection and Recognition. Models, Algorithms, and Networks PDF

Yali Amit

Two important subproblems of computer vision are the detection and recognition of 2D objects in gray-level images. This book discusses the construction and training of models, computational approaches to efficient implementation, and parallel implementations in biologically plausible neural network architectures. The approach is based on statistical modeling and estimation, with an emphasis on simplicity, transparency, and computational efficiency. The book describes a range of deformable template models, from coarse sparse models involving discrete, fast computations to more finely detailed models based on continuum formulations, involving intensive optimization. Each model is defined in terms of a subset of points on a reference grid (the template), a set of admissible instantiations of these points (deformations), and a statistical model for the data given a particular instantiation of the object present in the image. A recurring theme is a coarse-to-fine approach to the solution of vision problems. The book provides detailed descriptions of the algorithms used as well as the code, and the software and data sets are available on the Web.

Humans can perform object recognition and semantic segmentation pretty well even in photographs or on a computer screen where we don’t have depth data. Infact we can do this even when those photographs grossly disobey scale relationships. Anyways,

6.34 MB Taille du fichier
9780262011945 ISBN
2D Object Detection and Recognition. Models, Algorithms, and Networks.pdf


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Notes actuelles

Sofya Voigtuh

27/09/2002 · 2d objects detention and recognition Models, algorithms, and networks Yali Amit (0 avis) Donner votre avis. 320 pages, parution le 27/09/2002 Livre papier. 53,00 € Indisponible Résumé "Modeling the human ability to identify objects in images has proved to be a significant challenge. While computer vision researchers have largely concentrated on the geometric aspects of the problem such as Deep Exemplar 2D-3D Detection by Adapting from Real to ...

Mattio Müllers

05/02/2016 · The goal of object detection is to detect all instances of objects from a known class, such as people, cars, or faces in an image. Typically, only a small number of instances of the object are present in the image, but there is a very large number of possible locations and scales at which they can occur and that need to somehow be explored.

Noels Schulzen

Tutorial: Algorithms For 2-Dimensional Object Recognition.

Jason Leghmann

2D object detection and recognition: models, algorithms and networks 关联书籍. 搜索同名书籍. 豆瓣评分: 作者: Yali Amit 出版时间:2002. 页数:325 Object detection with neural networks — a simple …

Jessica Kolhmann

This book discusses the construction and training of models, computational ... 2D Object Detection and Recognition: Models, Algorithms, and Networks.