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DICTA
2009
14 years 17 days ago
SIFTing the Relevant from the Irrelevant: Automatically Detecting Objects in Training Images
Many state-of-the-art object recognition systems rely on identifying the location of objects in images, in order to better learn its visual attributes. In this paper, we propose fo...
Edmond Zhang, Michael Mayo
CRV
2009
IEEE
158views Robotics» more  CRV 2009»
14 years 6 months ago
Automated Spatial-Semantic Modeling with Applications to Place Labeling and Informed Search
This paper presents a spatial-semantic modeling system featuring automated learning of object-place relations from an online annotated database, and the application of these relat...
Pooja Viswanathan, David Meger, Tristram Southey, ...
CVPR
2007
IEEE
15 years 1 months ago
Semantic Hierarchies for Visual Object Recognition
In this paper we propose to use lexical semantic networks to extend the state-of-the-art object recognition techniques. We use the semantics of image labels to integrate prior kno...
Marcin Marszalek, Cordelia Schmid
CVPR
2007
IEEE
15 years 1 months ago
Beyond Local Appearance: Category Recognition from Pairwise Interactions of Simple Features
We present a discriminative shape-based algorithm for object category localization and recognition. Our method learns object models in a weakly-supervised fashion, without requiri...
Marius Leordeanu, Martial Hebert, Rahul Sukthankar