The bag-of-words (BoW) model treats images as an unordered set of local regions and represents them by visual word histograms. Implicitly, regions are assumed to be identically an...
Ramazan Gokberk Cinbis, Jakob J. Verbeek, Cordelia...
We propose semantic texton forests, efficient and powerful new low-level features. These are ensembles of decision trees that act directly on image pixels, and therefore do not ne...
In this paper, we propose an approach for TV commercial video classification by the categories of advertised products or services (e.g. automobiles, healthcare products, etc). Sin...
We propose using the proximity distribution of vectorquantized local feature descriptors for object and category recognition. To this end, we introduce a novel "proximity dis...
Although fully generative models have been successfully used to model the contents of text documents, they are often awkward to apply to combinations of text data and document met...