Year: 2005
Type: report
Abstract: We investigate the learning of the appearance of an object from a single image of it. Instead of using a large number of pictures of an object to be recognized, we use pictures of other objects to learn invariance to noise and variations in pose and illumination. This acquired knowledge is then used to predict if two images of objects unseen during training actually display the same object. We propose a generic scheme called chopping to address this task. Using a fast learner, we build hundreds of arbitrary binary splits of the image space designed to assign the same label to all the training images of any given object.
Authors: François Fleuret, Gilles Blanchard
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2153747924