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...
Abstract. In this paper we present a boosting based approach for automatic detection of micro-calcifications in mammographic images. Our proposal is based on using local features e...
Arnau Oliver, Albert Torrent, Meritxell Tortajada,...
Feature misalignment in object detection refers to
the phenomenon that features which re up in some
positive detection windows do not re up in other pos-
itive detection windo...
Zhe Lin (University of Maryland at College Park), ...
: A new method is presented to learn object categories from unlabeled and unsegmented images for generic object recognition. We assume that each object can be characterized by a se...
Andreas Opelt, Axel Pinz, Michael Fussenegger, Pet...
This paper contributes a new boosting paradigm to achieve detection of events in video. Previous boosting paradigms in vision focus on single frame detection and do not scale to v...