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DICTA
2009
14 years 11 months 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
SIBGRAPI
2008
IEEE
15 years 4 months ago
Benchmark for Quantitative Evaluation of Assisted Object Segmentation Methods to Image Sequences
Evaluation of segmentation methods applied to image sequences consists in the analysis of such methods according to quantitative and/or qualitative criteria, usually driven to som...
Franklin César Flores, Roberto de Alencar L...
CVPR
2011
IEEE
14 years 1 months ago
Effective 3D Object Detection and Regression Using Probabilistic Segmentation Features in CT Images
3D object detection and importance regression/ranking are at the core for semantically interpreting 3D medical images of computer aided diagnosis (CAD). In this paper, we propose ...
Le Lu, Jinbo Bi, Matthias Wolf, Marcos Salganicoff
DAGM
2006
Springer
15 years 1 months ago
Analysis on a Local Approach to 3D Object Recognition
Abstract. We present a method for 3D object modeling and recognition which is robust to scale and illumination changes, and to viewpoint variations. The object model is derived fro...
Elisabetta Delponte, Elise Arnaud, Francesca Odone...
ICIP
2002
IEEE
15 years 11 months ago
Modeling object classes in aerial images using hidden Markov models
A canonical model is proposed for object classes in aerial images. This model is motivated by the observation that geographic regions of interest are characterized by collections ...
Shawn Newsam, Sitaram Bhagavathy, B. S. Manjunath