Discriminative Training for Object Recognition Using Image Patches
- 1 January 2005
- proceedings article
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 2, 157-162
- https://doi.org/10.1109/cvpr.2005.134
Abstract
We present a method for automatically learning discriminative image patches for the recognition of given object classes. The approach applies discriminative training of log-linear models to image patch histograms. We show that it works well on three tasks and performs significantly better than other methods using the same features. For example, the method decides that patches containing an eye are most important for distinguishing face from background images. The recognition performance is very competitive with error rates presented in other publications. In particular, a new best error rate for the Caltech motorbikes data of 1.5% is achieved.Keywords
This publication has 10 references indexed in Scilit:
- Content-based Image Retrieval in Medical ApplicationsMethods of Information in Medicine, 2004
- Local context in non-linear deformation models for handwritten character recognitionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2004
- Object recognition using segmentation for feature detectionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2004
- Enhancements for local feature based image classificationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2004
- Object class recognition by unsupervised scale-invariant learningPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Selection of scale-invariant parts for object class recognitionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Example-based object detection in images by componentsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2001
- Unsupervised Learning of Models for RecognitionPublished by Springer Nature ,2000
- Wavelet-based salient points for image retrievalPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2000
- Generalized Iterative Scaling for Log-Linear ModelsThe Annals of Mathematical Statistics, 1972