Издательство: | Книга по требованию |
Дата выхода: | июль 2011 |
ISBN: | 978-3-6390-1380-1 |
Объём: | 172 страниц |
Масса: | 282 г |
Размеры(В x Ш x Т), см: | 23 x 16 x 1 |
Designing a general purpose computer vision system with performance comparable to that of the human vision system is the goal of many researchers. This book introduces a local appearance method, termed coherency filtering, which allows for the robust detection and analysis of rigid objects contained in heterogeneous scenes by properly exploiting the wealth of information returned by a k-nearest neighbours (k-NN) classifier. A significant advantage of k-NN classifiers is their ability to indicate uncertainty in the classification of a local window by returning a list of k candidate classifications. Classification of a local window can be inherently uncertain when considered in isolation since local windows from different objects may be similar in appearance. In order to robustly identify objects in a query image, a process is needed to appropriately resolve this uncertainty. Coherency filtering resolves this uncertainty by imposing constraints across the colour channels of a query image along with spatial constraints between neighbouring local windows in a manner that produces reliable classification of local windows and ultimately results in the robust identification of objects.
Данное издание не является оригинальным. Книга печатается по технологии принт-он-деманд после получения заказа.