69 search results - page 7 / 14 » SIFTing the Relevant from the Irrelevant: Automatically Dete... |
CVPR
2009
IEEE
14 years 2 months ago
2009
IEEE
Landmark labeling of training images is essential for many learning tasks in computer vision, such as object detection, tracking, and alignment. Image labeling is typically conduc...
ICIP
2003
IEEE
14 years 9 months ago
2003
IEEE
With the rapid technological advances in machine learning and data mining, it is now possible to train computers with hundreds of semantic concepts for the purpose of annotating i...
VMV
2001
13 years 8 months ago
2001
We present a novel approach to localization of objects in clutter images with the use of linear adaptive filters in a two-object classifier: target object versus clutter object. A...
CVIU
2006
13 years 7 months ago
2006
This paper describes how a visual system can automatically define features of interest from the observation of a large enough number of natural images. The principle complements t...
NIPS
2001
13 years 8 months ago
2001
We describe an algorithm for automatically learning discriminative components of objects with SVM classifiers. It is based on growing image parts by minimizing theoretical bounds ...