This chapter presents an approach for texture and object recognition that uses scale- or affine-invariant local image features in combination with a discriminative classifier. Text...
We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a weakly-supervised manner: the model is learnt from examp...
We introduce a stochastic model to characterize the online computational process of an object recognition system based on a hierarchy of classifiers. The model is a graphical netwo...
We present a component-based system for object detection and identification. From a set of training images of a given object we extract a large number of components which are clust...
Bernd Heisele, Ivaylo Riskov, Christian Morgenster...
Traditional approaches to object detection only look at local pieces of the image, whether it be within a sliding window or the regions around an interest point detector. However, ...
Kevin P. Murphy, Antonio B. Torralba, Daniel Eaton...