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CLOR
2006
13 years 9 months ago
Object Detection and Localization Using Local and Global Features
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...
MAMMO
2010
Springer
13 years 7 months ago
A Boosting Based Approach for Automatic Micro-calcification Detection
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,...
CVPR
2009
IEEE
15 years 19 days ago
Multiple Instance Feature for Robust Part-based Object Detection
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), ...
ICPR
2004
IEEE
14 years 6 months ago
Object Recognition Using Segmentation for Feature Detection
: 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...
ICCV
2005
IEEE
13 years 11 months ago
TemporalBoost for Event Recognition
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...
Paul Smith, Niels da Vitoria Lobo, Mubarak Shah