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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
GBRPR
2005
Springer
15 years 3 months ago
A Graph-Based, Multi-resolution Algorithm for Tracking Objects in Presence of Occlusions
One of the main difficult problem in video analysis is to track moving objects during a video sequence, especially in presence of occlusions. Unfortunately, almost all the differ...
Donatello Conte, Pasquale Foggia, Jean-Michel Joli...
IJCV
2008
266views more  IJCV 2008»
14 years 10 months ago
Learning to Recognize Objects with Little Supervision
This paper shows (i) improvements over state-of-the-art local feature recognition systems, (ii) how to formulate principled models for automatic local feature selection in object c...
Peter Carbonetto, Gyuri Dorkó, Cordelia Sch...
PAMI
2012
13 years 12 days ago
Recursive Segmentation and Recognition Templates for Image Parsing
— Language and image understanding are two major goals of artificial intelligence which can both be conceptually formulated in terms of parsing the input signal into a hierarchi...
Long Zhu, Yuanhao Chen, Yuan Lin, Chenxi Lin, Alan...
ICIAP
2001
Springer
15 years 10 months ago
2D Shape Recognition by Hidden Markov Models
In Computer Vision, two-dimensional shape classifcation is a complex and well studied topic, often basic for three-dimensional object recognition. Object contours are a widely cho...
Manuele Bicego, Vittorio Murino